MR-B3RB-M

The lower chassis comes partially assembled with the side skirts attached, the side plastic attached, the PDB partially wired, and the LED lighting installed and wired. Remove screws that hold on the side plates and also the screws that hold on the top plate. The screws holding the side skirts and top plate on top will be replaced with Thumbscrews . KEEP these M3x5mm screws for attaching the MR-CANHUBK344 to the top plate later

Lower chassis out of the box.

Remove top plate screws

Use a hex screwdriver or Allen Key and remove all top screws securing the top plate to the metal frame and carefully set them aside.

This is the draft online guide for MR-B3RB-M Pre-Production version.

Please excuse our "dust" while this gitbook is under construction. Supportive feedback is welcome: iain.galloway@nxp.com

Welcome to the MR-B3RB Assembly Guide!

Are you ready to embark on an exciting journey into the world of robotics? Meet MR-B3RB – your very own robot companion that you can build from scratch! Whether you're a seasoned tech enthusiast or just starting out, this guide will walk you through every step of the way.

What is MR-B3RB?

MR-B3RB stands for "Mobile Robotics - Buggy 3 Revision B." It's an educational mobile robotics platform designed to ignite your curiosity and expand your understanding of robotics, programming, and engineering. By assembling MR-B3RB, you'll not only gain hands-on experience but also develop problem-solving skills and technical knowledge that are essential in today's tech-driven world.

Why Build MR-B3RB?

• Hands-On Learning: Dive into the practical aspects of robotics, electronics, and programming.

• Skill Development: Sharpen your critical thinking, creativity, and technical skills.

• Fun and Engaging: Experience the joy of building and bringing your own robot to life.

• Community Support: Join a community of like-minded individuals passionate about technology and innovation.

What You'll Find in This Guide

• Step-by-Step Instructions: Detailed, easy-to-follow steps to assemble and program your MR-B3RB.

• Visual Aids: Diagrams, images, and videos to guide you through each stage of the process.

• Troubleshooting Tips: Solutions to common issues to ensure a smooth assembly experience.

• Additional Resources: Links to materials, tools, and further learning opportunities.

So, what are you waiting for? Let's get started on this exciting adventure and bring your MR-B3RB to life

Block Diagram: Power Distribution Board

The PDB (Power Distribution board) is where both power enters from the battrey , and also provides a number of connector "translations" to match the motor and LED lighting. Specialized connectors on the motor and encoder to translate to the Dupont-style or standard DroneCode connector pinouts. It should be noted that the block diagram above does not show ALL the power distribution connections, which are as follows:

• Battery input through a fuse

• Battery voltage and current measurement through the INA226

• 3x Battery voltage outputs on 5 pin JST-GH for NavQPlus, MR-CANHUBK344, Extra

• 5V regulating supply for LED lights, and powering PWM servo rail on MR-CANHUBK344 and therefore the Servo itself.

• PWM signals are consolidated into a single XHDP connector for ease of connection.

Block Diagram: GPS Module

The GPS combines UART, I2C for Compass, and GPIO for switches, LED, and Beeper into a single large DroneCode standard connector.

Block Diagram: Debugging interfaces

The DCD-LZ interface simply combines SWD and a UART on a single JST-GH Dronecode connector. Depending on your kit you may have any of the following debug adapter boards:

• FTDI USB-UART cable and adapter for UART/Console on the NavQPlus

• FTDI USB-UART cable + DCD-LZ adapter for MR-CANHUBK344 DCD-LZ interface

• In some systems you will find NeuralProbe board with USBC interface and connectors for UART/Console AND DCD-LZ interface. This board includes a USB-UART converter and also includes a button that will toggle the RST pin on SWD/JTAG interface. There is a 3rd interface on this board for Pixhawk V6X debug+uart connectors (not used here, used with NXP MR-VMU-RT1176)

MR-B3RB-M ("Medium/Main")

The following pages describe the mechanical assembly of the MR-B3RB-M version. The -M version of MR-B3RB includes the -MUK mechanical upgrade kit consisting of:

• Front and rear plastics (for LED covers and angles front and rear covers)

• Lidar arch plate metal and metal top cover.

To install the -MUK (Mechanical Upgrade kit) you will need to first:

• Remove the plastic clips that hold the top metal plate in place and

• Replace them with the side skirt plastic.

• Then install the front and rear plastics as shown in the following assembly videos.

• (This will change in production version. Side skirts will already be present in base version)

MR-B3RB-S ("Small/Standard" Pre Production)

You may have a -S version of the kit which doesn't include these extra components, in that case just mount the NavQPlus and MR-CANHUBK344 in a similar way as shown in the assembly videos.

There is a plastic bracket included with the NavQPlus kit that can be used to mount the camera in the correct location at the front.

The gears are adjusted at the factory and this should not need to be done on a new B3RB. However over time it may be that they need adjustment. Follow this procedure to re-adjust the gear meshing. Diagnose Motor Gear Meshing Issue

1. Rotate the Wheels Gently: Start by gently rotating the wheels of the B3RB that the motor is driving.

2. Listen Carefully: Listen to the sound of the gears as you rotate the wheels. Ideally, the gears should mesh smoothly without any grinding or excessive noise.

3. Feel for Resistance: As you rotate the wheels, feel for any resistance or unevenness. This could indicate that the gears are not meshing properly.

Adjust the Gear Mesh

1. Locate the Motor Mounting Bracket: Identify the motor mounting bracket where the motor is attached to the chassis or frame of your device.

2. Loosen the Adjustment Screws: Typically, there are two screws at the front of the motor mounting bracket that secure the motor in place. Use an appropriate screwdriver to gently loosen these screws. You don’t need to remove them completely, just enough to allow slight movement of the motor.

3. Adjust the Motor Position: Apply mild pressure to the motor in the direction that will improve the gear meshing. This usually means pushing the motor closer to the gear or slightly adjusting its angle to ensure the teeth of the gears are aligned properly.

4. Check and Tighten: After adjusting, rotate the wheels again and listen for any improvement in the gear meshing. Once satisfied with the adjustment, carefully tighten the screws back into place to secure the motor in its adjusted position.

Standoff for LIDAR arch stability

There is a orange or black 3d printed plastic standoff post which also acts to protect the cable. The file will also be provided in 3D Printed parts page See image below

Introduction

MR-CANHUBK344 is the real time controller board for the robot. After successfully attaching the NavQPlus, the next step is to install the MR-CANHUBK344 evaluation board.

Assemble MR-CANHUBK344 onto top plate

The MR-CANHUBK344 board should be attached in the highlighted holes of the following image. Reuse the M3x5mm screws that were previously removed from the side skirts. M3x5mm screws should be used to screw in from the bottom side.

Be cautious to not squeeze the wires attached to the NavQPlus!

Upon completion, the entire assembly should appear as follows:

History

MR-B3RB is short for Mobile Robotics - Buggy3 Revision B. This is the second revision to a robotic vehicle called . Some people didn't like calling a product "buggy". So even though Buggy3 is a brave name, we decided to instead make it MR-B3RB as it is a nice and friendly robot like R2D2.

We took lessons learned from that platform and applied them as an upgrade for 2024.

The upgrades of the MR-B3RB are:

• Uses the same rugged metal base RC car, with readily available replacement and upgrade parts

• No need to change the steering servo

• Upgraded BLDC motor with gear reduction, integrated ESC (motor controller) and quadrature encoder output that can be used for vehicle odometry

• Metal upper chassis that can be removed as a module

• Power distribution board with additional connector matching and power supply for boards and servos.

• Removeable mounting plate for companion computer, real time processors, communications radios and any other add on components

• RGB addressable lighting

• Optional upgrade to plastic sides, front, rear and lidar arch mount

• Optional GPS / remote Magnetometer/ arming button

Currently this is the PRE-Production version, there will still be some updates coming to improve the modularity of the top plate, and provide additional mounting for user added 3d printed components.

Attach the NavQPlus camera to the front plastic mount.

The camera housing included with the NavQPlus mounts to the front "GoPro" style mount on the front plastic:

The camera flex cable should come out the back of the NavQPlus and loop over top of it. Then route under the lower edge of the front bracket. and up into the camera module. The final setup should look like this:

Front and rear plastic

Screw the front and rear plastic to the top plate using two M3x5 screws from the bottom

The camera flex cable should already be attached to the front plastic.

Introduction

The Quadrature decoder (QDEC) cable connects from PDB to MR-CANHUBK344. The actual quadrature signals are coming from the encoder on the motor itself. The PDB is used to interface between the different cable types. This signal provides information on how many revolutions, and therefore how far, the robot has travelled and is used in the control system as an input.

QDEC (Quadrature Decoder) Cable

This cable is crucial for calculating the odometry, speed and direction of the robot car. The cable should look like this:

One end of the cable must be attached to the QDEC out pin on the PDB:

And the other end must be attached to the following pin on the MR-CANHUBK344:

The MR-B3RB is versatile and can support several network wiring configurations. There are also several optional connections. This section will serve to show the BASELINE connections. We will also attach cables that may not be used, but should stay with the B3RB for future expansion

Baseline wiring intentions

• Provide power to the NavQPlus and MR-CANHUBK344

• Connect the two with T1 Ethernet

• Attach the LIDAR to the NavQPlus

• Attach the SERVO and Motor Control PWM to the MR-CANHUBK344

• Quadrature encoding from the motor/PDB to the MR-CANHUBK344

• Connect the RGB LED lighting

• Have debuggers and consoles attached

• Optionally plug in unused RC-PWM input

• Optionally connect CAN-FD cables, which could be used for peripherals and attachments

• (Optionally) connect a serial console from the MR-CANHUBK344 to the NavQPlus <<TODO - add link to section that removes the jumper on the PDB. Add PDB wiring section>>>

The final setup with al the established connections should look like this: <<<TODO UPDATE PHOTOS FROM HERE ON >>>

A closer view on the connection on MR-CANHUBK344:

And in the NavQPlus:

Please follow the steps 3a and 3b for the detailed explanation on these connections.

Wiring instructions will be demonstrated using images and GIFs for clearer visualization of the process.

Introduction

The RGB LEDS communicate using a modified SPI type that is unidirectional. The power for the LEDs is supplied by the PDB, and the SCL SDA lines attach to a SPI port on the MR-CANHUBK344

RGB LED wiring

First, we'll show hot to connect the LEDs cables from the LEDs panels to the PDB and the MR-CANHUBK344.

• Use the 4-pin cable with a protective covering to connect from the front to the rear LED assembly ends.

• Connect the rear LED to the PDB (Power Distribution Board) and the MR-CANHUBK344.

The following image shows the LED lights setup with the left side representing the rear and the right side indicating the front of the car.

The following images show a zoomed vision of the wiring:

The remaining pin is this one:

That must be connected on the following pin of the MR-CANHUBK344:

If you have correctly followed these steps the wiring setup of the LEDs cables should be finished.

Introduction

The NavQPlus and MR-CANHUBK344 communicate to each other using 100Base-T1 Two wire ethernet .

BaseT1 Ethernet wiring between NavQPlus and MR-CANHUBK344

• Connect the ethernet cable between the NavQPlus and the MR-CANHUBK344.

• Zip Tie the cable at both ends, and tuck it under the top plate.

• Note the specific side notches to use.

• Use a piece of tape to hold it neatly out of the way under the plate

Introduction

The GPS module is primarily used to provide the Magnetometer, sound and SAFETY button for the system. Not all systems will use the GPS localization functionality. The software however does injest the data and can be used for navigation outdoors.

M10 GPS connection

The M10 GPS cable attaches to the MR-CANHUBK344 as shown below

Introduction

The kit may include an ARMING board and/or a GPS module. In addition to being used for GPS, the it does also include a arming/safety switch and a beeper. Generally if you have a GPS, it is preferred to use that rather than the ARMING board.

PX4 Arming Board vs GPS

The arming board will provide the same beeper and arming buttons. It does not (currently) include a compass component.

Install M10 GPS module

If provided in your kit, please install the GPS and GPS post mounting, The the pieces needed are listed in the WITB GPS Module page.

There is a set of screws that comes with the GPS unit. Use the 4 longer screws and Nylock Lock Nuts to attach the base mount.

It should be placed in this furthest back position:

Attach the mounting mast rod and fasten it with one of the smaller two screws left. At this time keep the screws only loosely tightened. Attach the top mount with the remaining screw. Keep it only loosely tighened as well. It should look like this when completed:

Attach the M10 GPS module to the mast

Locate the M10 GPS and the 3M double tape.

Attach the double tape in the center of the top mount.

Carefully align the GPS in the center of this tape. Ensure the arrow on the GPS module is facing forward. The cable of the GPS should be zip tied so it stays very close to the GPS mast in order to not obstruct the LIDAR sensor.

Now mount the NavQPlus and the MR-CANHUBK344 to the metal top plate. Follow the steps in the next two sections. The final setup will look like this:

Power Cable

The cable shown below is NOT USED in B3RB. Instead connect the 5 pin power cable to the corresponding point on the PDB

Connect the l5 pin (4 wire) JST-GH power cable to the NavQPlus Power input:

BaseT1 Ethernet wiring between NavQPlus and MR-CANHUBK344

This is also explained here: #baset1-ethernet-wiring-between-navqplus-and-mr-canhubk344

Lidar connection

<TODO> refer to the mounting of the LIDAR base

The cable necessary for connect the NavQPus to the LIDAR-STL-27 is the number one in WITB Cables and Screws.

A closer view of this cable:

The Lidar used is the following:

You should connect the smaller end of the cable to the Lidar and the bigger end to the UART3 Serial port of the NavQPlus:

Thse are all the connections available for NavQPlus:

<TODO >

• note on CAN

• note on console

• note on Ethernet

After connecting all the cables, proceed to attach the metal board frame to the robot car using the screws you removed at the beginning of this tutorial:

Front Plastic Shield with Mount for Camera

Please attach the plastic shield with the camera housing to the robot's front using 1cm M2.5 screws, which are located in this box provided:#m2-m2.5-m3-screw-fastener-kit-for-wltoys-144001-1-14-rc-s.no.-25.

For reference, a picture of the screws is displayed here: <<<TODO - these are not the correct screws. They should be flat head (tapered head> screws. Take picture and add here>>>

The mounting must look like these pictures:

Back Plastic Shield

And the attach the back plastic shield of the robot with the same screws:

Lidar arch metal upper plate

<<<<TODO - update the pictures below. The orientation of the LIDAR is backward!!!>>>

Attach the arch metal upper plate and the Lidar with 4 of the screws M3 X 0.5 X 10MM with socket head, labelled with the number six in the following picture:

It should look like this:

And the connection to the NavQPlus, as explained in #lidar-connection is depicted in this image:

Decorative top cover

METAL UPPER

LIDAR,

FINAL TOUCHES AND STICKERS

Introduction

There are two locations where on board batteries could be located, inside the "mezzanine" level of the frame and on the lower side opposite the motor side of the lower chassis.

Since any battery in the mezzanine level will be challenging to remove and likely could only be charged in place, we will only be referring to the removeable battery location on he lower chassis.

Securing the battery

The exact method of securing the battery is dependent on the user preferences.

• There is a battery strap included in the kit. This could also be used to strap to the upper/mezzanine level of the metal frame.

• You may wish to remove the small plastic battery tray frame that is already installed in the kit in order to make more space.

• A foam piece can be used to wedge between the underside of the battery and the lower chassis in order to prevent any movement. This wedges the battery "up" against the underside of the mezzanine level.

• 3D printed pieces may be designed also to hold the battery in a preferred way.

LiPo Battery Specification

Typically we are using an off-the-shelf LiPo battery pack similar to what is used in RC airplanes and Quadcopters. In addition to ensuring the battery chosen fits the compartment area, the battery should have the following specifications:

1. LiPo 3s (Three Cell) 12V nominal voltager (10-14V)

2. 2000-3000mAh

3. XT60 connector with balance leads

4. Dimensions

   A) 75mm L x 34mm W x 26 H (short and stubby)

   B) 100-110mm L x 35mm W x 22-26mm H (longer format)

Links to sample batteries

Below are links to some example batteries. THIS IS IN NO WAY an endorsement of these specific batteries, only a link so you can see more detail about the types of similar batteries that could be used:

Stubby / Shorty type battery pack

Zeee 3S 2200mAh Lipo Battery 11.1V 50C Shorty Pack Battery with XT6...Zeee 3S 2200mAh Lipo Battery 11.1V 50C Shorty Pack Battery with XT60 Plug for RC Car Truck RC Vehicles Boat Drone RC Airplane Quadcopter Helicopter FPV Racing Hobby Models(2 Pack)

HOOVO 3S Lipo Battery 2200mAh 80C 11.1V Shorty Lipo Battery Pack So...HOOVO 3S Lipo Battery 2200mAh 80C 11.1V Shorty Lipo Battery Pack Softcase with XT60 Connector Compatible with Drone RC Airplane Helicopter Quadcopter FPV RC Car,2 Pack

Longer format battery pack

LiPo Battery charger

You must use a LiPo battery charger to safely charge the battery. There are very inexpensive ones available that will charge using the cell termination connectors at the expense of them being quite slow to charge. Many other types of chargers exist. When choosing a charger consider that this is a safety issue, and overcharging or improperly charging can be dangerous and result in a fire.

There are many excellent LiPo battery chargers available. ISDT makes several high end charges like the following: (This is an example, and not a specific recommendation)

https://www.amazon.de/dp/B07QDML2K2/ref=sspa_dk_detail_5?psc=1&pd_rd_i=B07QDML2K2&pd_rd_w=hq5Gd&content-id=amzn1.sym.1a5ede13-ac41-41fa-9f3a-776fb14b38e3&pf_rd_p=1a5ede13-ac41-41fa-9f3a-776fb14b38e3&pf_rd_r=M8HGEXYRP2Z80EBH2WXG&pd_rd_wg=yP7Nh&pd_rd_r=5299dfb0-8df2-4cfc-ab85-b13813ad1a74&sp_csd=d2lkZ2V0TmFtZT1zcF9kZXRhaWxfdGhlbWF0aWM

The top cover doubles as a work stand. This will keep the wheels up of the gound and can be useful while testing. You may want to put some soft tape or foam on the underside of the buggy chassis in order to avoid possible scratches on the top cover.

Introduction

This assembly is performed by the manufacturer. It is included here for completeness.

Base Mechanical Frame assembly

MR-B3RB-BMF out of box assembly Video

Link: https://a360.co/4bVC8pm

MR-B3RB units have a power monitor built into the PDB board. This will tell you the total pack voltage and individual cell voltage. It will alarm when the cell voltage goes too low.

Press the button on top to set the ALARM voltage to 3.2volts The Battery monitor is connected as shown below

This section details the assembly process for the small version of MR-B3RB. This version comprises the base mechanical frame, the NavQPlus board equipped with the integrated camera, a mounting piece designed for the camera, as well as the MR-CANHUBK344 board and its Adap board.

The assembly of this smaller version is notably simpler. The primary steps involve mounting the NavQPlus and the MR-CANHUBK344, as explained in this section of the B3RB-M assembly guide Step 2: Mounting the boards to the metal frame. Note that there are certain parts of the tutorial that do not require your attention:

• Do NOT Remove the Camera Mount from the NavQPlus: It is essential to retain the camera mount on the NavQPlus.

• GPS Module and LiDAR Standoff Installation: You do not need to install the GPS module or the standoff for LiDAR stability.

• The step 2e is also not necessary: Step 2e: Attach front and rear plastic to top plate

• Wiring Tutorial: Follow the wiring tutorial( Step 3: Wiring), but be aware that you will not be using LED, GPS, or LiDAR cables. However, the QDEC cable, the Ethernet connection between the NavQPlus and the CANHUBK344, as well as the PWM and power cables, remain unchanged.

Do NOT remove the camera mount form the NavQPlus:

After following these instructions, proceed to mount the camera to the metal frame:

Utilize the set of screws provided in the NavQPlus box.

Attach the camera mount in the specified position:

Upon completion of these steps, the B3RB-S version of the robot should resemble the following:

This section is for items that may be useful for the end user, but are part of the manufacturing and kitting before the user gets a B3RB. They are not part of the normal assembly process.

This checklist is prepared for training units that will be shipped elsewhere This is a checklist for use if you have already assembled a unit and need to ship it to another location. It is to ensure the recipient has all the components needed, and the kit will be functional.

Short checklist for shipping

• Wires are zip tied in place

• QDEC wire is connected

• T1 connected between NavQPlus and MR-CANHUBK344

• CONSOLE cable is attached to NavQPlus. Tuck it in place.

• CONSOLE/DEBUG (DCD-LZ) cable is attached to CANHUBK344. Tuck it in place

• RGBLED wires are zip tied or taped up and not dangling

• NavQPlus Antenna is tucked under plastic but over metal

• Check that the rotating battery plug mount moves freely

• NXP, small Cognipilot, med Cognipilot, Emcraft stickers applied

Changes before shipment

• GPS module removed and packed under rear of buggy

• Check all screws are in place including thumbscrews

• Disassemble and tuck GPS module and MAST in place

• Invert LIDAR plate and lidar for shipping. Plastic Lidar Jack secure.

• Wipe down

• REMOVE:

  • USBA to USBC cable (only USBC-C is allowed)

  • original FLAT battery plug mount

  • If present - the two original RGB LED cables

• Add XT60 unsoldered male connector (Temporary addition)

Critical support components that must be in box

• JLINK debugger + DCD-LZ + FTDI Cable (note console/debug cable attached to buggy)

• Serial console cable for NavQPlus. FTDI + adapter board (Console cable attached to buggy)

• Cognipilot Neuralprobe

• Battery alarm

• IX Industrial Ethernet to RJ45 cable

Photos and videos of the checklist items

Checklist items before shipping

Changes to make before shipment

Ensure these critical items are included

Put them in a single bag.

REMOVE the following components if present

CogniPilot introduction

CogniPilot is a new opensource vehicle control software that sits cleanly on top of the Zephyr RTOS. This will be used as the default real-time vehicle controller software framework on MR-B3RB kits.

EVEN when not using the full capability of CogniPilot, the framework still includes many software modules, high level drivers, communications methods and related PC tools and setup that makes other less demanding uses (such as NXP-CUP) much easier. The framework is there and can be used as much or as little as needed.

Zephyr and CogniPilot

Zephyr RTOS has build targets for MR-CANHUBK344 and MR-VMU-RT1176 which can be used as part of the real-time controller and IMU for MR-B3RB. In various versions of MR-B3RB kits these boards may already be included.

CogniPilot info

CogniPilot's claim to fame is that the control system software component is synthesized as a module from popular control software called Casadi. Casadi is popular with control systems engineers and researchers and allows the decoupling of the control theory, simulation and mathematical proofs from the actual code that implements the particular controller math. This approach helps with ensuring safety and robustness, while also supporting rapid innovation

CasADi

CasADi is an open-source tool for nonlinear optimization and algorithmic differentiation.

It facilitates rapid — yet efficient — implementation of different methods for numerical optimal control, both in an offline context and for nonlinear model predictive control (NMPC).

https://web.casadi.org/

CogniPilot Cerebri module

CogniPilot represents the name of the group of software modules making up the vehicle control system. More details of what each of the modules does is available on the project website.

Cerebri represents the CogniPilot control-system software module and is named similarly to a human brain cerebellum, which "processes and regulates signals between other parts of your brain and body, and is involved in coordinating functions of your body (for example, walking)." The synthesized code from CasADi, or code representing the control theory-module for the particular vehicle intended, plugs into CogniPilot's Cerebri module. The control system for the vehicle type is a swappable module, it can define control functions or approaches that relate to a ground vehicle vs a multicopter, vs a winged vehicle. You then separately provide a hardware description file for the specific vehicle characteristics.

Example:

One of many control theories could be used to control an Ackermann steering car. The specific control theory is built in CasADi. Code is then synthesized and put into Cerebri for execution. The control theory was for a generic Ackermann vehicle type. The hardware description file defines the power of the motors, the size of the vehicle and wheels, the placement of all these wheels. You could theoretically have an Ackermann vehicle where the steering is misaligned with the drive wheel thrust. This same control software works for a passenger car or a toy car since the vehicle size and power that gets defines independently. A different synthesized control theory would be loaded to control a multicopter. The hardware definition would control the arm lengths, the number and orientation of the motors, and the thrust from the motors.

CogniPilot information

There is much more detail and information about the design and structure of CogniPilot here: https://www.cognipilot.com

The developer guide for CogniPilot can be found here: https://cognipilot.org/releases/airy/getting_started/install

Overview

Cognipilot software module operate across multiple processors in order to form a complete system:

• CogniPilot Electrode - Runs on PC host groundstation with Linux/ROS2

• CogniPilot Corti and Nav2 - Runs on NavQPlus Embedded companion computer running Linux/ROS2

• CogniPilot Synapse - Bridge over Ethernet, running on CANHUBK344 and NavQPlus

• CogniPilot Cerebri - CANHUBK344 real time control MCU running Zephyr with ZROS nodes and topics

(DRAFT)

Block Diagram of the NavQPlus

<todo> insert a block diagram and or photo of wiring. Image below may be helpful

Wiring instructions will be demonstrated using images and GIFs for clearer visualization of the process.

RGB LED wiring

First, we'll show hot to connect the LEDs cables from the LEDs panels to the PDB and the MR-CANHUBK344.

• Use the 4-pin cable with a protective covering to connect from the front to the rear LED assembly ends.

• Connect the rear LED to the PDB (Power Distribution Board) and the MR-CANHUBK344.

The following image shows the LED lights setup with the left side representing the rear and the right side indicating the front of the car.

The following images show a zoomed vision of the wiring:

The remaining pin is this one:

That must be connected on the following pin of the MR-CANHUBK344:

If you have correctly followed these steps the wiring setup of the LEDs cables should be finished.

QDEC (Quadrature Decoder) Cable

This cable is crutial for calculating the odometry, speed and direction of the robot car. The cable should look like this:

One end of the cable must be attached to the QDEC out pin on the PDB:

And the other end must be attached to the following pin on the MR-CANHUBK344:

BaseT1 Ethernet wiring between NavQPlus and MR-CANHUBK344

Second, we'll show how to connect the ethernet cable between the NavQPlus and the MR-CANHUBK344.

PWM cable wiring to MR-CANHUBK344

The PWM cables that come from the MR-CANHUBK344 board to the Power Distribution Board should look like this.

Servo cable color code

The cable color code is as follows:

Ensure the cable is oriented so that the white PWM signal is connection the port labelled (S) on the MR-CANHUBK344. This is "inboard" on the PCB. The black ground wire will be closest to the outboard edge of the PCB.

The PWM cable that connects to the servo must be connected to PWM0 of the MR-CANHUBK344 as depicted in the following GIF:

The PWM cables that correspond to the motor throttle (PWM 1) and motor ENB (PWM2) must be connected on the following pins on the PDB:

The other end of the cables must be located in this position of the MR-CANHUBK344:

The following GIF shows the connection of the three cables:

Note that an extension cable is used for the servo PWM. The cable on the servo is the alternative coloring as shown in the table above.

Power cable from PDB to MR-CANHUBK344

The last cable to connect is the EXTRA LONG power cable from the MR-CANHUBK344 to the Power Distribution Board which looks like this. The normal length power cable can be similarly connected to the NavQPlus

This is how it must be connected to the PDB:

And the other end must be connected to this pin on the MR-CANHUBK344

The following picture depicts the connections in an animated way.

M10 GPS connection

This is the M10 GPS

And this is all the cable connections available for now.

Prepare: Lidar mounted to metal LIDAR Arch

The screws below and nylon locking nuts are included in the LIDAR box. Use these to attach the LIDAR to the LIDAR Arch.

Connect LIDAR cable to NavQPlus UART

Attach the arch metal upper plate and the Lidar with 4 of the screws M3 X 0.5 X 10MM with socket head, labelled with (6) in the following picture:

<<<TODO - move the lidar connection link details to this single page. Delete the other references>>

First chose option A or B

Option A: Dual Lock mounting the NavQPlus on the metal frame

Option B: Mounting the NavQPlus on the metal frame

Alternative mounting using screws

The kit includes DUAL LOCK type mounting, eliminating the need for the procedure below and screw fastening. This will also elevate the NAVQPLUS boards slightly so that Ethernet and USB will have better clearance. We strongly recommend you just use some DUAL LOCK Velcro instead of screwing the NavQPlus to the metal frame.

An alternative method of mounting is to use the provided M3 screws to securely attach the board's corners to the following position in the metal frame:

Screw them in from the bottom side. It should look like this:

Then wire the cables: NavQPlus Cable management on top plate

Use a ziptie to secure the power cable (4 wire cable with 5 pin JST-GH), and route the CAN cables down and underneath as shown below.

After successfully attaching the NavQPlus, the next step is to install the MR-CANHUBK344 evaluation board.

Introduction

There are two 5 pin JST-GH cables that provide battery power to the MR-CANHUBK344 and the NavQPlus. They are 5 pins, with no wire in the center position. Two wires are battery voltage+ and two wires are battery voltage-. Be sure to limit the voltage applied at the battery to <20V or the specified ratings for any boards plugged in. The nominal battery voltage is expected to be ~12V,

Power cable from PDB to MR-CANHUBK344

• Connect is the EXTRA LONG power cable from the MR-CANHUBK344 to the Power Distribution Board.

• The normal length power cable can be similarly connected to the NavQPlus

• ZIP TIE the cables to the edge of the top plate and make them neat.

These cable connect to the 5 pin JST GH on the PDB. Either connector is ok. They are both the same.

And the other end must be connected to this pin on the MR-CANHUBK344

The following picture depicts the connections in an animated way.

M10 GPS connection

This is the M10 GPS

And this is all the cable connections available for now.

Introduction

The MR-CANHUBK344 sends PWM signals to the Motor controller and also to the Servo. These are standard RC Model type PWM connections. It is important to get the positions correct on the header as the PWM signal timings are different between the motor and the steering servo. Also note that the steering servo gets powered from the +5V that is PROVIDED by the motor PWB connection on the PDB board.

PWM cable wiring to MR-CANHUBK344

The PWM cables that connect between the MR-CANHUBK344 board and the Power Distribution Board should look like this. Two of them are Female-Female and one is Male-Female.

Servo cable color code

The cable color coding is as follows:

EXTRA CARE NEEDED

The PWM cable must be oriented so that the white signal wire is connection the pin labelled (S) on the MR-CANHUBK344.

The wite wire should be "inboard" on the PCB. The black ground wire will be closest to the outboard edge of the PCB.

Steering Servo PWM cable connection

The PWM cable that connects to the servo must be connected to PWM 0 of the MR-CANHUBK344. This is the PWM header CLOSEST to the side of the board with the CAN connectors.

This is depicted in the following GIF:

Motor control PWM cable connection

<<TODO>> make it more clear which cable is which. There is also a debug procedure that can be added. IF the motor starts running immediately on power up, then PWM 1 and PWM 2 need to be swapped. Confirm - This is when only ONE of the PWMs are connected.

The PWM cables that correspond to the motor throttle (PWM 1) and motor ENB (PWM2) must be connected on the following pins on the PDB:

The other end of the cables must be located in PWM 1 and PWM 2 positions of the MR-CANHUBK344:

The following GIF shows the connection of the three cables:

Power cable from PDB to MR-CANHUBK344

The last cable to connect is the EXTRA LONG power cable from the MR-CANHUBK344 to the Power Distribution Board which looks like this. The normal length power cable can be similarly connected to the NavQPlus

This is how it must be connected to the PDB:

And the other end must be connected to this pin on the MR-CANHUBK344

The following picture depicts the connections in an animated way.

M10 GPS connection

This is the M10 GPS

And this is all the cable connections available for now.

Introduction

The full robotics reference design experience on MR-B3RB relies on the Linux NavQPlus companion computer working in concert with the real time controller MR-CANHUBK344. CognipPilot is the preferred framework that works hand in hand with ROS2 to provide a fully robotic vehicle, and sets up and configures the majority of the associated host companion computer, and development PC tools. The CogniPilot system is therefore more than just the Cerebri real time vehicle control module.

Installation and setup overview

A) Prepare your Linux development PC

Follow this section of Cognipilot to prepare your Linux development PC with ROS, Zephyr and Cognipilot development tools :

NEW

B) Prepare NavQPlus

Follow this section of to prepare Cognipilot-Cranium on NavQPlus :

NEW

C) Prepare MR-CANHUBK344 real time vehicle controller

Next Steps

After installation, you are ready to use the MR-B3RB.

• You can log into the NavQPlus and even into the MR-CANHUBK344 running CogniPilot/Zephyr

• You can run ROS SIL or "real hardware" examples using RVIZ or Foxglove as a control station.

• The vehicle is capable of being safely armed through several steps and autonomously navigating to a position and pose as specified/pointed to on the control station software.

Links

Introduction

Base Mechanical Frame assembly

MR-B3RB-BMF (Pre-Production) assembly Video

Bill of materials

Procedure

1. Gather the buggy aluminum cage, the PDB board and the PDB mount.

Introduction

Prepare your Linux development PC

Please start with an Ubuntu Linux install 22.04 or newer.

Follow this section of CogniPilot to prepare your Linux development PC with ROS, Zephyr and CogniPilot development tools https://airy.cognipilot.org/getting_started/install/

NEW https://brave.cognipilot.org/getting_started/install/ Ubuntu Linux 24.04

This will:

1. Setup ssh keys and gpg keys for git access

2. install Git

3. Install ROS2

4. install Zephyr build tools

5. and B3RB CogniPilot packages on your host Linux laptop.

6. prepare a SIL (software in the loop) example

7. optionally setup for serving the CogniPilot documentation locally

Next Steps

At this point you have configured a Linux PC for development. Follow the remaining subpage steps for guidance to get the B3RB (CANHUB-K3 and NavQPlus ready) to be updated. Note that the next section to refer to in the CogniPilot will be https://airy.cognipilot.org/reference_systems/b3rb/setup/

NEW https://brave.cognipilot.org/reference_systems/b3rb/setup/

Introduction

Prepare NavQPlus

Follow this section to prepare CogniPilot-Cranium on NavQPlus: https://airy.cognipilot.org/cranium/compute/navqplus/setup/

NEW https://brave.cognipilot.org/cranium/compute/navqplus/setup/

This will:

1. Flash the EMMC on the NavQPlus with the current Linux Image, using uuu using the USB interface

2. Establish a console connection using one of the three possible methods (USB-UART, SSH,USB-C Gadget ethernet)

3. Connect NavQPlus to a Wi-Fi network and establish an alternative console via SSH over Wi-Fi connection

4. Install CogniPilot Cranium on the NavQPlus (using the script provided)

Links

The developer guide for CogniPilot can be found here: https://cognipilot.org/releases/airy/getting_started/install

NEW https://brave.cognipilot.org/reference_systems/b3rb/setup/

Introduction

Prepare MR-CANHUBK344 real-time vehicle controller

Follow this section of CogniPilot to prepare Cognipilot-Cerebri on MR-CANHUBK344: https://airy.cognipilot.org/reference_systems/b3rb/setup/

https://airy.cognipilot.org/reference_systems/b3rb/about/

NEW: https://brave.cognipilot.org/reference_systems/b3rb/setup/

NEW: https://brave.cognipilot.org/reference_systems/b3rb/about/

This will:

1. Update MR-CANHUBK344 with the Zephyr+Cognipilot-Cerebri image. (Cerebri is the application, Zephyr is the RTOS. They are flashed simultaneously using a prepared image.)

First connect MR-CANHUBK344 to J-LinkEDU Mini

You need to follow this guide to correctly flash Cerebri onto the board: Connect J-Link EDU Mini to MR-CANHUBK344 with DCD-LZ adapt board

Software Setup for MR-CANHUBK344

cd ~/cognipilot/ws/cerebri
west update
cd ~/cognipilot/ws/cerebri/app/b3rb
west build -b mr_canhubk3 -p
west flash

Next Steps

At ths point you are ready to use the MR-B3RB.

You can log into the NavQPlus and even into the MR-CANHUBK344 running CogniPilot/Zephyr

You can run ROS SIL or "real hardware" examples using RVIZ or Foxglove as a control station.

The vehicle is capable of being safely armed through several steps and autonomously navigating to a position and pose as specified/pointed to on the control station software.

Execution

Software Procedure

MR-CANHUBK344

When booted, MR-CANHUBK344 should display the following CogniPilot logo and welcome screen on the console.

uart:~$
                                          ▄▄▄▄▄▄▄▄
         ▄▄▄▄▄ ▄▄▄▄▄                    ▀▀▀▀▀▀▀▀▀
     ▄███████▀▄██████▄   ▀█████████████████████▀
  ▄██████████ ████████ ▄   ▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄▄
 ███████████▀ ███████▀ ██   ▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀
█████████▀   ▀▀▀▀▀▀▀▀ ████   ▀███████████▀
▀█████▀ ▄▄███████████▄ ████   ▄▄▄▄▄▄▄▄▄
  ▀▀▀ ███████████████▀ ████   ▀▀▀▀▀▀▀▀
       ▀▀█████▀▀▀▀▀▀  ▀▀▀▀   ▄█████▀
               ████████▀    ▄▄▄
               ▀███▀       ▀▀▀
                ▀▀
╔═══╗╔═══╗╔═══╗╔═╗ ╔╗╔══╗╔═══╗╔══╗╔╗   ╔═══╗╔════╗
║╔═╗║║╔═╗║║╔═╗║║║║ ║║╚╣╠╝║╔═╗║╚╣╠╝║║   ║╔═╗║║╔╗╔╗║
║║ ╚╝║║ ║║║║ ╚╝║║╚╗║║ ║║ ║║ ║║ ║║ ║║   ║║ ║║╚╝║║╚╝
║║   ║║ ║║║║╔═╗║╔╗╚╝║ ║║ ║╚═╝║ ║║ ║║   ║║ ║║  ║║
║║ ╔╗║║ ║║║║╚╗║║║╚╗║║ ║║ ║╔══╝ ║║ ║║ ╔╗║║ ║║  ║║
║╚═╝║║╚═╝║║╚═╝║║║ ║║║╔╣╠╗║║   ╔╣╠╗║╚═╝║║╚═╝║ ╔╝╚╗
╚═══╝╚═══╝╚═══╝╚╝ ╚═╝╚══╝╚╝   ╚══╝╚═══╝╚═══╝ ╚══╝
       ┏━━━┓┏━━━┓┏━━━┓┏━━━┓┏━━┓ ┏━━━┓┏━━┓
       ┃┏━┓┃┃┏━━┛┃┏━┓┃┃┏━━┛┃┏┓┃ ┃┏━┓┃┗┫┣┛
       ┃┃ ┗┛┃┗━┓ ┃┗━┛┃┃┗━┓ ┃┗┛┗┓┃┗━┛┃ ┃┃
       ┃┃ ┏┓┃┏━┛ ┃┏┓┏┛┃┏━┛ ┃┏━┓┃┃┏┓┏┛ ┃┃
       ┃┗━┛┃┃┗━━┓┃┃┃┗┓┃┗━━┓┃┗━┛┃┃┃┃┗┓┏┫┣┓
       ┗━━━┛┗━━━┛┗┛┗━┛┗━━━┛┗━━━┛┗┛┗━┛┗━━┛

Within a few seconds, the red light on the T1-Ethernet port on both the boards should light up.

NavQPlus

ros2 launch b3rb_bringup robot.launch.py

Links

The developer guide for CogniPilot can be found here: https://cognipilot.org/releases/airy/getting_started/install

NEW https://brave.cognipilot.org/reference_systems/b3rb/setup/

Launch Notes for B3RB:

Serial terminal

# serial terminal to NavQPlus

screen /dev/ttyUSB0 115200

Setup WiFi connection

# Setup wifi hotspot on phone.

# same network as host PC

# show local wifi networks, find the one you want

sudo nmcli device wifi # for a text interface sudo nmtui

# Connect NavQPlus Wifi to network

sudo nmcli device wifi connect <network name> password <password>

FoxGlove open connection command

When Foxglove starts, "Open Connection" and type connect to ws://b3rb-xx.local:4242 (replace b3rb-xx with whatever your buggy's hostname is)

SSH Login

# SSH login to NavQPlus

ssh user@mrb3rb

#or

ssh user@mrb3rb.local

ROS2 Launch commands

# FIRST launch Ros2 electrode on host pc

# Then launch Ros2 on B3RB

ros2 launch b3rb_bringup robot.launch.py

Set a ROS Domain ID

If there are multiple vehicles being used at the same time on the same network, then you will also need to set a unique ROS_DOMAIN_ID for on both the host LInux machine and the NavQPlus edit your file ~/.bashrc using VIM, NANO or GEDIT

change the line (find with CTRL+W) export ROS_DOMAIN_ID=xxx

where xxx is a unique number from the other robots

First take the J-Link EDU Mini, you can find more information here: #j-link-edu-mini-debugger

Then, get the J-Link EDU Mini. Then, use the cable with a micro USB connector on one end and a USB Type-A connector on the other end.

Then take the 10-Pin 2x5 Socket-Socket IDC (SWD) Ribbon Cable and connect it to the J-Link EDU mini:

Please, connect the 10-Pin 2x5 Socket-Socket IDC (SWD) Ribbon cable in the following position to the J-Link EDU Mini:

Next, please pick up the DCD-LZ adapt board:

Next, connect one end of the 10-pin 2x5 Socket-Socket IDC (SWD) ribbon cable to the connector on the DCD-LZ adapt board. Ensure that the orientation of the connector corresponds to the one shown in the following image:

The pick the 7 position JST-GH connector:

Finally, connect one end to the DCD-LZ adapt board and the other end of the 7 position JST-GH connector to the MR-CANHUBK344. Please, connect it into the pin showed in the following image:

Now, you just need to connect the USB cable to your development computer and also remember to connect the LiPo battery to the PDB to flash the MR-CANHUBK344, as the board needs to be connected to the power. Then, you can return here to follow the instructions: #prepare-mr-canhubk344-real-time-vehicle-controller

First take the J-Link EDU Mini, you can find more information here: #j-link-edu-mini-debugger

Then, get the J-Link EDU Mini. Then, use the cable with a micro USB connector on one end and a USB Type-A connector on the other end.

Then take the 10-Pin 2x5 Socket-Socket IDC (SWD) Ribbon Cable and connect it to the J-Link EDU mini:

Please, connect the 10-Pin 2x5 Socket-Socket IDC (SWD) Ribbon cable in the following position to the J-Link EDU Mini:

Next, please pick up the Cognipilot debug adapter:

Next, connect one end of the 10-pin 2x5 Socket-Socket IDC (SWD) ribbon cable to the connector on the Cognipilot debugger. Ensure that the orientation of the connector corresponds to the one shown in the following image:

Finally, connect the other end of the 7 position JST-GH connector to the MR-CANHUBK344. Please, connect it into the pin showed in the following image:

Now, you just need to connectConnect the USB cable to your development computer and also remember to connect power to the Buggy (the LiPo battery to the PDB) in order to flash the MR-CANHUBK344, as the board needs to be connected to the power. Then, you can return here to follow the instructions: . #prepare-mr-canhubk344-real-time-vehicle-controller

Connect the MR-Link-MR to the 7 position JST-GH programing connector to the MR-CANHUBK344. Please, connect it as shown in the following image:

Now, you just need to connect the USB cable to your development computer and also remember to connect the LiPo battery to the PDB to flash the MR-CANHUBK344, as the board needs to be connected to the power. Then, you can return here to follow the instructions: #prepare-mr-canhubk344-real-time-vehicle-controller

Sometimes you just want to start over. It's ok, we all have days like that. I Fyou need afresh cognipilot start, and want to be extra sure there are no leftover dependencies or files you dont' want etc then follow these steps. Keep in mind this is going to erase local changes you may have made to cognipilot files. Note them in advance if you want to re-do the changes afterwards. (for example you may have disabled the battery voltage check in <todo> xxx.conf)

For clean install on your PC

Then start again with the

or this link

Stuck on a previous Gazebo

The instructions above will take care of Gazebo install also. If you happen to know you are stuck on an old version of Gazebo you may want to just try this first. The example below is where gazebo "garden" (gzgarden) is installed, but you want gazebo "harmonic"

DRAFT-DRAFT-DRAFT Connect the MR-Link-MR to the 7 position JST-GH programing connector to the MR-CANHUBK344. Please, connect it as shown in the following image: <todo> update image to show MR-Link-MR <todo> alternatively connect the 10 pin JTAG/SWD ribbon cable connector <todo update photos below

Connect the USB cable to your development computer and also remember to connect power to the Buggy (the LiPo battery to the PDB) in order to flash the MR-CANHUBK344.

Zephyr West : MCU-Link-MR (using pyOCD)

Use this command when programming using the MCU-Link or MCU-Link-MR from Zephyr west tool

west flash --runner pyocd

Building, Flashing and Debugging — Zephyr Project Documentation

Introduction

Introduction

At ths point you are ready to use the MR-B3RB. If you have reviewed the documentation you should now:

• You can log into the NavQPlus console and even into the MR-CANHUBK344 running CogniPilot/Zephyr

• You can run ROS SIL or "real hardware" examples using RVIZ or Foxglove as a control station.

• The vehicle is capable of being safely armed through several steps and autonomously navigating to a position and pose as specified/pointed to on the control station software.

Operation of ROS-CogniPilot

Software Procedure

MR-CANHUBK344

OPTIONAL: When booted, if you have a console connected, MR-CANHUBK344 will display the following CogniPilot logo and welcome screen on the console.

Within a few seconds, the red light on the T1 Ethernet port on both the boards should light up.

Linux Host PC

(The definitive guide is on cognipilot.org !! copied here for convenience only)

• From the command line run

NavQPlus

• Login to the NavQPlus using ssh or serial console.

• Ensure the NavQPlus and Host PC are on the same network

• AFTER starting ROS on the Host PC, THEN on the NavQPlus run

Links

This section explains the essential software required for participating in the NXP Cup 2024 using the MR-B3RB Robot.

Participants will use a combination of pre-configured ROS2 and Zephyr-Cerebri software. Here, "Cerebri" refers to the application layer, while "Zephyr" is the underlying Real-Time Operating System (RTOS). This software stack integrates with the Cognipilot autopilot system, which is available at .

The following pages provide detailed installation instructions for both the simulation environment and the actual robot. Additionally, there is a section dedicated to explaining the line follower algorithm for the NXP Cup 2024.

If your installation has been successful you must be able the launch the Gazebo simulation by running the following commands in your development computer:

Launching the Gazebo Harmonic simulation will enable you to control the robot via the Foxglove interface. As explained in this section:

Explanation of repository to be updated

Next, we will install all necessary packages for developing the algorithm for the NXP CUP 2024, applicable to both the MR-b3rb simulation and the actual robot.

To simplify repository updates, we've created a shell script. This script automates the process of updating all repositories to the latest versions hosted on the GitHub, specifically for the NXP Cup.

The changes on the repositories are:

• Synapse Protobuf and Synapse Tinyframe: Define the Pixy Vector message in the Protobuf language and provide essential definitions and functions for the TinyFrame library to operate correctly. For more information, refer to the documentation.

• Synapse msgs and Synapse ros: Extend ROS with the Pixy Vector message definition and support Synapse which the facilitates communication between NavQPlus (ROS2) and CANHUBK344 (Zephyr).

• Dream world: Adds a simulated race track environment to the workspace.

• B3RB simulator: Includes the launch file for the node that processes the race track images.

• Electrode: Integrates support for the debug image and pixy vector in Foxglove, facilitating debugging and visualization.

• Cerebri: Implements a subscribing mechanism to receive the Pixy Vector message and controls for the line follower algorithm.

• NXP CUP Vision: Added ROS2 package for processing race track images, transforming perspectives, detecting track edges, and publishing both the debug image and the Pixy Vector, pivotal for visual processing.

Bash script to update the repositories

This file ensures that all the repositories are updated. Save this script in ~/cognipilot:

Save this script as update_repos_native.sh in the ~/cognipilot directory, using any text editor of your choice, such as Vim, Gedit, Nano, or VSCode.

Building cranium, electrode and cerebri

Then, open the terminal and execute the following commands:

This must have updated all your repositories. Please review the output of this script. It's possible that you have made local changes to the repositories, and you may need to stash them.

To build the software, navigate to the cranium/src directory within ~/cognipilot:

Repeat the build process for the electrode directory:

Update the West workspace for cerebri.

Testing the update

Now, you are ready to run the simulation:

To launch the Gazebo simulation featuring the MR-B3RB robot on a simple raceway, execute:

To start the Foxglove viewer for the simulation, run:

These commands will initiate the Gazebo simulation with the MR-B3RB robot and the raceway, alongside launching the Foxglove viewer.

To initiate the robot's movement, press the AUTO button and the arm button on the joystick. This action will activate the robot's line-following mode and set it to the armed state, preparing it for operation.

Once the AUTO and arm buttons on the joystick are pressed, the robot will immediately begin to navigate around the racetrack. To understand the underlying code and setup, and to explore ways to obtain a better performance for the NXP CUP 2024, proceed to the next tutorial.

User contributed 3d printed parts may be linked to here

Try playing with this option for performing flip without 2D

gst-launch-1.0 v4l2src device=/dev/video0 extra-controls='c,horizontal_flip=1,vertical_flip=1' ! xxxxx

The MR-B3RB platform is equipped with a camera connected to the NavQPlus, enabling a variety of functions such as robot visualization, Visual SLAM, and other computer vision and machine learning applications. The Cognipilot package for ROS2 includes an 'ov5645.ini' configuration file with the camera's intrinsic calibration data. This data is crucial for correcting lens distortion and understanding the camera's geometric properties in computer vision and robotics applications. However, this file serves is just an indication, and users must perform a camera calibration after assembling the MR-B3RB robot to ensure a better operation.

Introduction and background

Some cameras, such as pinhole cameras, introduce significant distortion to images. Two major kinds of distortion are radial distortion and tangential distortion.

Radial distortion causes straight lines to appear curved. Radial distortion becomes larger the farther points are from the center of the image. Similarly, tangential distortion occurs because the image-taking lense is not aligned perfectly parallel to the imaging plane. So, some areas in the image may look nearer than expected. In short, we need to find five parameters, known as distortion coefficients.

Extrinsic parameters corresponds to rotation and translation vectors which translates a coordinates of a 3D point to a coordinate system

To find these parameters, we must provide some sample images of a well defined pattern (e.g. a chess board). We find some specific points of which we already know the relative positions (e.g. square corners in the chess board). We know the coordinates of these points in real world space and we know the coordinates in the image, so we can solve for the distortion coefficients. For better results, we need at least 10 test patterns.

In addition to this, we need to some other information, like the intrinsic and extrinsic parameters of the camera. Intrinsic parameters are specific to a camera. They include information like focal length and optical centers. The focal length and optical centers can be used to create a camera matrix, which can be used to remove distortion due to the lenses of a specific camera. The camera matrix is unique to a specific camera, so once calculated, it can be reused on other images taken by the same camera.

Camera calibration example procedure.

After the theoretical background we are going to see how to calibrate the camera on the MR-B3RB robot.

Connect through ssh to the NavQPlus as explained in Cognipilot: CheatSheet for operation

Install necessary packages

sudo apt update

sudo apt install ros-humble-camera-calibration-parsers

sudo apt install ros-humble-camera-info-manager

sudo apt install ros-humble-launch-testing-ament-cmake

Install b3rb_camera_calibration package

cd ~/cognipilot/cranium/src

git clone https://github.com/NXPHoverGames/b3rb_camera_calibration

cd ~/cognipilot/cranium/

colcon build --symlink-install --packages-select b3rb_camera_calibration

source ~/cognipilot/cranium/install/setup.sh

Start calibration procedure

In one terminal run the following command:

ros2 launch b3rb_camera_calibration b3rb_camera_calibration_launch.py 

Then open a new terminal and connect throush ssh to the NavQPlus and run:

ros2 run b3rb_camera_calibration cameracalibrator --size 9x6 --square 0.02 --ros-args -r image:=/camera/image_raw -p camera:='chessboard'

If you want to see the output yo can run in your host computer:

ros2 launch electrode electode.launch.py

This will open foxglove and you will be able to select the topic /calibration_camera_feed on the image panel.

You should be able to see something like this.

Calibration procedure

For the calibration process, it's advised to keep the robot stationary and move the calibration pattern to different positions instead. Place it at various angles, because the calibration system requires multiple samples and poses to calibrate accurately.

You will see the 'Continue Sampling' message in the terminal until the calibration process has collected enough samples. After that, the message will switch to 'READY TO CALIBRATE.' Additionally, the 'calibrate' text in the Foxglove image will change to blue, as shown in the image below:

Finish calibration

After the calibration node has collected enough samples, you'll need to open a new terminal window. Then, connect to the NavQPlus via SSH to begin calculating the camera matrix. In this new terminal, execute the following command to start the calibration:

ros2 topic pub /calibration_control std_msgs/msg/String "data: 'start_calibration'" --once

For saving the results please run the following command:

ros2 topic pub /calibration_control std_msgs/msg/String "data: 'save_results'" --once

Then you must see a message similar to the following:

Then the calibration has successfully finished, to stop the calibration please run:

ros2 topic pub /calibration_control std_msgs/msg/String "data: 'stop'" --once

View the results

To see the calibration results, first navigate to the cognipilot folder:

cd ~/cognipilot

Then create a new folder:

mkdir calibration_data

And uncompress the file and place the files in this new folder:

tar -xzvf calibrationdata.tar.gz -C calibration_data/

The files ost.txt and ost.yaml contain the camera matrix and distortion parameters.

Calibration pattern

You have to print a calibration pattern, this tutorial is going to be done with a 9x6 chessboard pattern, but you can do it with other pattern. This web allows you to choose the one that you prefer: https://calib.io/pages/camera-calibration-pattern-generator

This is the one used in this tutorial: https://github.com/opencv/opencv/blob/4.x/doc/pattern.png

Please print it in an A4 mantaining the original size.

This page explains the software required for the NXP CUP 2024 with the MR-B3RB robot.

The CogniPilot software is integrated into both the NavQPlus, within ROS2, and the MR-CANHUBK344, within the Zephyr RTOS together forming an Ackermann steering robotic development platform.

Please follow the installation instructions to obtain the modified branch of the CogniPilot software, specifically tailored for the NXP CUP 2024; these instructions are explained in the previous sectionNXP-CUP 2024: Simulation Install instructions

ROS2 brief explanation

The ROS2 part of the software is designed for high-level tasks and should be treated as "black box" for the NXP-CUP 2024,meaning that its code should not be modified.If you encounter any errors in this code, please report them to the NXP Cup organizers or through the technical support channel on the official NXP CUP Discord: https://discord.gg/JcWPbw649S.

The main CogniPilot modification in the ROS2 side for the NXP Cup 2024 is addition of the nxp_track_vision node, which receives camera data, transforms the perspective, and extracts the Pixy Vector message. This message consists of two vectors, each with a tail and a head, defining the borders of the race track. This information is used by the robot controller to ensure that the robot stays within the track boundaries.

Here's the definition of the Pixy Vector ROS2 message:

std_msgs/Header header
# Vector 0 head and tail points
uint32 m0_x0    # Tail of vector @ x
uint32 m0_y0    # Tail of vector @ y
uint32 m0_x1    # Head of vector @ x
uint32 m0_y1    # Head of vector @ y

# Vector 1 head and tail points
uint32 m1_x0    # Tail of vector @ x
uint32 m1_y0    # Tail of vector @ y
uint32 m1_x1    # Head of vector @ x
uint32 m1_y1    # Head of vector @ y

The std_msgs/Header in the Pixy Vector ROS2 message includes the timestamp indicating when the message was sent. Additionally, the message is composed by two vectors, with each vector represented by a pair of points: one indicating where the vector begins (tail) and the other where it ends (head). Each of these points is defined by an x and a y value, specifying their position in a two-dimensional space.

The nxp_track_vision_node also publishes the Camera Debug Image. This image shows the perspective transformation applied to the camera's view, along with the detected lines of the track. Additionally, it displays the vectors being sent by the track vision node. This visual feedback should result helpful for debugging and optimizing the robot;s control software.

This is an example of the debug camera image:

You can visualize this image through Foxglove. For doing that first run:

ros2 launch electrode electrode.launch.py #sim:=true (If you are using simulation)

Then add an Image panel to the B3RB layout provided and configure the ROS2 topic to /nxp_cup/debug_image.

Control algorithm through Cerebri

Now a explanation of the line following control algorithm will be done. This algorithm is located on the Cerebri running on the Zypher RTOS in the MR-CANHUBK344. The Cerebri acts as the brain of our operation, facilitating complex decision-making processes that guide the robot seamlessly along the track.

This code is what you must modify and improve for the NXP CUP 2024.

The main function of the line follower algorithm is located in the velocity state inside the finite state machine logic that manages the robot's behaviour. This file is located in the ~/cognipilot/ws/cerebri/app/src/velocity.c

This is the GitHub location: See code.

The application folder is where the vehicle finite state machine, control, and estimation code reside. For more information visit: https://airy.cognipilot.org/cerebri/platforms/rovers/

In that folder you will find a file called velocity.c. This code is written in C language and has two main operation modes: the cmd_vel modes which listens the /cmd_vel topic from the Nav2 node from ROS2 and the auto mode, this one will listen to the Pixy vector message sendt by the nxp_track_vision_node and will estimate the velocity needed to maintain the robot in the race track:

// Follow line function in velocity.c
static void follow_line(context* ctx)
{
    double frame_width = 78;
    double frame_height = 51;
    double window_center = frame_width / 2;
    double linear_velocity=0.7;
    double angular_velocity=-0.6;
    double single_line_steer_scale=0.6;

    double x = 0.0;
    double y = 0.0;

    double steer = 0.0;
    double speed = 0.0;
     
    int num_vectors = 0;
    if(!(ctx->pixy_vector.m0_x0 == 0 && ctx->pixy_vector.m0_x1 == 0 && ctx->pixy_vector.m0_y0 == 0 && ctx->pixy_vector.m0_y1 == 0)) {
        num_vectors++;
    }
    if(!(ctx->pixy_vector.m1_x0 == 0 && ctx->pixy_vector.m1_x1 == 0 && ctx->pixy_vector.m1_y0 == 0 && ctx->pixy_vector.m1_y1 == 0)) {
        num_vectors++;
    }
    
    switch(num_vectors) {
        case 0:
            speed = 0.0;
            steer = 0.0;
            break;
        case 1:
            if(ctx->pixy_vector.m0_x1 > ctx->pixy_vector.m0_x0) {
                x = (ctx->pixy_vector.m0_x1 - ctx->pixy_vector.m0_x0) / frame_width;
                y = (ctx->pixy_vector.m0_y1 - ctx->pixy_vector.m0_y0) / frame_height;
            } else {
                x = (ctx->pixy_vector.m0_x0 - ctx->pixy_vector.m0_x1) / frame_width;
                y = (ctx->pixy_vector.m0_y0 - ctx->pixy_vector.m0_y1) / frame_height;
            }

            if((ctx->pixy_vector.m0_x0 != ctx->pixy_vector.m0_x1) && ((y > 0.0) || (y <0.0))) {
                steer = -angular_velocity * (x / y) * single_line_steer_scale;
            } else {
                steer = 0.0;
            }
            speed = linear_velocity;
            break;
        case 2:
            if((ctx->pixy_vector.m1_x0 >= ctx->pixy_vector.m1_x1) && (ctx->pixy_vector.m0_x0 <= ctx->pixy_vector.m0_x1)){
                steer = angular_velocity * (((ctx->pixy_vector.m0_x1 + ctx->pixy_vector.m1_x1) / 2.0) - window_center) / frame_width;
            }else if ((ctx->pixy_vector.m1_x0 < ctx->pixy_vector.m1_x1) && (ctx->pixy_vector.m0_x0 <= ctx->pixy_vector.m0_x1)){
                steer = angular_velocity * (((ctx->pixy_vector.m0_x1 + ctx->pixy_vector.m1_x0) / 2.0) - window_center) / frame_width;
            }else if ((ctx->pixy_vector.m1_x0 > ctx->pixy_vector.m1_x1) && (ctx->pixy_vector.m0_x0 > ctx->pixy_vector.m0_x1)){
                steer = angular_velocity * (((ctx->pixy_vector.m0_x0 + ctx->pixy_vector.m1_x1) / 2.0) - window_center) / frame_width;
            }else {
                steer = angular_velocity * (((ctx->pixy_vector.m0_x0 + ctx->pixy_vector.m1_x0) / 2.0) - window_center) / frame_width;
            }

            speed = linear_velocity;      
            break;
    }
    
    double vel_linear_x = speed * (1 - fabs(2 * steer));  
     
    double turn_angle = 0;
    double omega_fwd = 0;
    double V = vel_linear_x;
    double omega = steer;
    double delta = 0;
    CASADI_FUNC_ARGS(ackermann_steering);
    args[0] = &ctx->wheel_base;
    args[1] = &omega;
    args[2] = &V;
    res[0] = &delta;
    CASADI_FUNC_CALL(ackermann_steering);

    omega_fwd = V / ctx->wheel_radius;
    if (fabs(V) > 0.01) {
        turn_angle = delta;
    }
    b3rb_set_actuators(&ctx->actuators, turn_angle, omega_fwd);
}

There are several important variables and functions that are used in the code. A key description of them is given below:

The switch instruction evaluates the number of vectors found in the camera image and what the robot car will do depending on this number:

Case: 0 vectors found

If no vectors are found (case 0), then the vehicle will stop.

Case: 1 vector found

If one vector is found, the algorithm finds the gradient of the vector and stores that in steer, and the speed

Case: 2 vectors found

If two vectors are found, then the example algorithm will find the offset in the x direction of the average of the two head points of each vector. This will give us a steering value that will steer the cup car in the correct direction, which will be stored in steer. The speed value will be calculated and is stored in speed.

After calculating the speed and the steer values, a call to the CASADI function is done to estimate the control variable for the actuators. Then the robot can move the necessary meters that you need.

Modifying the code

Before making changes to the velocity.c file or any files in the ~/cognipilot/ws/cerebri/app/b3rb directory, remember to rebuild the application to see the changes take effect.

For simulation:

cd ~/cognipilot/ws/cerebri 
west update
west build -b native_sim app/b3rb/ -p -t install

For real robot:

cd ~/cognipilot/ws/cerebri 
west update
west build -b mr_canhubk3 app/b3rb -p
west flash

Auto mode and Arming the robot automatically

In the nxp_track_vision.py file within the ROS2 package nxp_cup_vision, you'll find the following code snippet:

def statusCallback(self,data):
        #Putting robot in AUTO mode 
        if(data.mode!=2):
            joystick_msg=sensor_msgs.msg.Joy()
            joystick_msg.header.stamp=ROSClock().now().to_msg()
            joystick_msg.axes=[0.0,0.0,0.0,0.0]
            joystick_msg.buttons = [0, 1, 0, 0, 0, 0, 0, 0]
            #self.JoystickPub.publish(joystick_msg)
        #If robot is in AUTO mode -> arming the robot
        elif(data.mode==2 and data.arming!=2):
            joystick_msg=sensor_msgs.msg.Joy()
            joystick_msg.header.stamp=ROSClock().now().to_msg()
            joystick_msg.axes=[0.0,0.0,0.0,0.0]
            joystick_msg.buttons = [0, 0, 0, 0, 0, 0, 0, 1]
            #self.JoystickPub.publish(joystick_msg)

This code snippet automatically sets the B3RB robot in AUTO mode and arms the robot. By default, the self.JoystickPub.publish(joystick_msg) lines are commented out to allow control through Foxglove Studio during development. Uncomment these lines if you want the robot to automatically enter AUTO mode and arm itself.

If you need the robot to delay its start, add a sleep command:

sleep(15.0)

This makes the robot wait for 15 seconds before starting, which can be particularly useful for the NXP-CUP competition.

If you have correctly followed the previous steps, you should already be familiar with how to flash the Cognipilot software onto the MR-CANHUBK344 board. In this step, we will flash the board again, but this time with an updated version of the Cerebri software that includes support for the NXP Cup 2024. Additionally, we will need to log in via SSH to the NavQPlus and update the cranium workspace to enable support for the NXP Cup, similar to the procedure outlined on the previous page.

Build and flash the NXP-CUP Cerebri image for B3RB

In your development computer go to:

cd ~/cognipilot/ws/cerebri
git pull

cd ~/cognipilot/ws/cerebri
git status

Which should return:

On branch nxp-cup
Your branch is up to date with 'origin/nxp-cup'.

nothing to commit, working tree clean

If it doesn't show that:

git checkout nxp-cup

If you have ensured that you are on the nxp-cup branch and that there is not any update available. Then type the following command:

cd ~/cognipilot/ws/cerebri 
west update

Build NXP-CUP Cerebri B3RB image for MR CANHUBK3 with west

cd ~/cognipilot/ws/cerebri 
west build -b mr_canhubk3 app/b3rb -p

Flash Cerebri B3RB image with west to MR CANHUBK3

Make sure Segger JLink is on your system and the MR CANHUBK3 is connected to the JLink programmer: Connect J-Link EDU Mini to MR-CANHUBK344 with DCD-LZ adapt board.

cd ~/cognipilot/ws/cerebri 
west flash

Once it has finished, you can disconnect the J-Link from your computer and from the MR-CANHUBK344.

JLinkExe
connect
S32K344
S
4000
loadbin /home/$user/cognipilot/ws/cerebri/build/zephyr/zephyr.elf 0x400000
exit

Updating repositories on NavQPlus

Once you have flashed the MR-CANHUBK344, It's time to log into the NavQPlus. Do this with this command:

ssh <username>@<hostname>.local

Next, we will install the packages to develop the algorithm for the NXP CUP 2024 in the B3RB robot.

To simplify repository updates, we've created a shell script. This script automates the process of updating all repositories to the latest versions hosted on the NXPHoverGames GitHub, specifically for the NXP Cup.

The changes on the repositories are:

• Synapse Protobuf and Synapse Tinyframe: Define the Pixy Vector message in the Protobuf language and provide essential definitions and functions for the TinyFrame library to operate correctly. For more information, refer to the Synapse documentation.

• Synapse msgs and Synapse ros: Extend ROS with the Pixy Vector message definition and support Synapse which the facilitates communication between NavQPlus (ROS2) and CANHUBK344 (Zephyr).

• B3RB robot: Includes the launch file for the node that processes the race track images.

• NXP CUP Vision: Added ROS2 package for processing race track images, transforming perspectives, detecting track edges, and publishing both the debug image and the Pixy Vector, pivotal for visual processing.

This file ensures that all the repositories are updated. Save this script in ~/cognipilot:

#!/bin/bash

declare -A repos=(
    ["cranium/src/synapse_protobuf"]="https://github.com/NXPHoverGames/synapse_protobuf"
    ["cranium/src/synapse_tinyframe"]="https://github.com/NXPHoverGames/synapse_tinyframe"
    ["cranium/src/synapse_msgs"]="https://github.com/NXPHoverGames/synapse_msgs"
    ["cranium/src/synapse_ros"]="https://github.com/NXPHoverGames/synapse_ros"
    ["cranium/src/b3rb_robot"]="https://github.com/NXPHoverGames/b3rb_robot"
    ["cranium/src/nxp_cup_vision"]="https://github.com/NXPHoverGames/nxp_cup_vision"
)

# Update existing repositories or clone if they don't exist
for repo in "${!repos[@]}"; do
    echo "Processing $repo..."
    repo_path="${repo}" # Derive the full path
    
    # Check if the repository directory exists. If it does not, clone it.
    if [ ! -d "${repo_path}" ]; then
        echo "Repository ${repo_path} does not exist. Cloning..."
        git clone --branch nxp-cup "${repos[$repo]}" "${repo_path}"
        echo "Cloned ${repo} into ${repo_path}."
    fi
    
    # Navigate to the repository directory
    cd "${repo_path}" || { echo "Failed to change directory to ${repo_path}. Does it exist?"; continue; }
    
    # Set the new remote URL
    git remote set-url origin "${repos[$repo]}"
    echo "Remote changed to ${repos[$repo]}"

    # Fetch changes from the new remote
    git fetch origin
    echo "Fetched changes from origin."

    # Checkout the specific branch
    git checkout nxp-cup
    if [ $? -eq 0 ]; then
        echo "Checked out nxp-cup branch."
        # Pull the latest changes from the branch
        git pull origin nxp-cup
        echo "Pulled latest changes from nxp-cup branch."
    else
        echo "Failed to checkout nxp-cup branch. Does it exist?"
    fi
    
    # Return to the original directory
    cd - > /dev/null
done

Save this script as update_repos_navqplus.sh in the ~/cognipilot directory, using any text editor of your choice, such as Vim or nano.

Then, open the terminal and execute the following commands:

Change directory to ~/cognipilot and make the script executable:

cd ~/cognipilot
chmod +x update_repos_navqplus.sh
./update_repos_navqplus.sh

This must have updated all your repositories. Please review the output of this script. It's possible that you have made local changes to the repositories, and you may need to stash them.

To build the software, navigate to the cranium/src directory within ~/cognipilot:

cd ~/cognipilot/cranium/
colcon build --symlink-install
cd ~/cognipilot/cranium/
source install/setup.bash

Now, you are ready to operate the platform.

On the NavQPlus, run the B3RB launch file:

ros2 launch b3rb_bringup robot.launch.py

Start Foxglove for operation and data visualization run the following command in your development computersimulation, run:

ros2 launch electrode electrode.launch.py

These commands will initiate the algorithm on the MR-B3RB robot and Foxglove viewer. You should locate your robot in the racetrack.

To initiate the robot's movement, press the AUTO button and the arm button on the joystick. This action will activate the robot's line-following mode and set it to the armed state, preparing it for operation.

Once the AUTO and arm buttons on the joystick are pressed, the robot should immediately begin to navigate around the racetrack. To understand the underlying code and setup, and to explore ways to obtain a better performance for the NXP CUP 2024, proceed to the next tutorial.

CANHUB-ADAP is used with MR-B3RB to provide:

• An IMU

• SCARD

• Connections for StemmaQT/QUIIC I2C devices

• GPS connectors

• More

The schematics below can be used to review the interfaces

1. Introduction

2. Use cases

3. Connect the VIVE Tracker to a PC

4. Using in ROS2 with the libsurvive library

5. Annex: connect the VIVE tracker to a PC

6. References

Introduction

The Vive tracker can be used to provide a reasonably accurate ground truth reference for robotics. By enabling it using the libsurvive library, position and pose information can be viewed and stored in ROSBAGS for further analysis.

VIVE Tracker (3.0) can pair with HTC’s wireless dongle or use its USB interface to transfer tracking data to a PC. An accessory attached to VIVE Tracker (3.0) can:

• Simulate buttons of the VIVE Controller through the underlying Pogo pin port.

• Send specific data to a PC through the USB interface of VIVE Tracker (3.0).

How it works

Status lights

The status light shows:

• Green when the controller is in normal mode

• Blinking red when battery is low

• Blinking blue when the controller is pairing with the headset

• Blue when the controller is connecting with the headset

• Orange when charging

Use cases

As mentioned in the Developer guide [2], the VIVE Tracker provides five use cases:

• Use case 1: Track passive objects through USB interface in VR. In this case, the dongle is not used. VIVE Tracker (3.0) is connected to the PC through USB to directly transfer tracking data.

• Use case 2: Track passive objects through USB interface in VR, with the accessory passing data to a PC through USB, BT/Wi-Fi or propriety RF. This is similar to Use Case 1 but the accessory directly transfers the tracking data to a PC for a specific purpose based on its design.

• Use case 3: Track moving objects by wireless interface in VR. In this case, the dongle is used to transfer tracking data from the VIVE Tracker (3.0) to a PC.

• Use case 4: Track moving objects using a wireless interface in VR, with the accessory passing data to a PC through USB, BT/Wi-Fi or propriety RF. This is similar to Use Case 3 but the accessory directly transfer the tracking data to/from a PC for a specific purpose based on its design.

• Use case 5: Track moving objects using a wireless interface in VR, with the accessory simulating buttons of the VIVE Controller or passing data to a PC through the VIVE Tracker (3.0). This is similar to Use Case 3 but the accessory connects with the VIVE Tracker (3.0) to transfer a button event to a PC through the Pogo pins or USB interface.

Using with ROS2 and libsurvive library

To VIVE tracker in NavQPlus using ROS2, you need to follow the instructions in the following github repository: https://github.com/asymingt/libsurvive_ros2

libsurvive_ros2 provides a lightweight ROS2 wrapper around the libsurvive project, an open source set of tools and libraries that enable 6 dof tracking on lighthouse and vive based systems.

First of all set the udev rules:

sudo curl -fsSL https://raw.githubusercontent.com/cntools/libsurvive/master/useful_files/81-vive.rules \
    -o /etc/udev/rules.d/81-vive.rules
sudo udevadm control --reload-rules && sudo udevadm trigger

And install the required packages:

sudo apt-get install build-essential \
    cmake \
    freeglut3-dev \
    libatlas-base-dev \
    liblapacke-dev \
    libopenblas-dev \
    libpcap-dev \
    libusb-1.0-0-dev \
    libx11-dev \
    zlib1g-dev

Then create a workspace and install the ROS2 wrapper:

mkdir -p ~/ros2_ws/src
cd  ~/ros2_ws/src
git clone https://github.com/asymingt/libsurvive_ros2.git
cd ..
colcon build
source install/setup.bash

Connect the VIVE Tracker to the NavQPlus using an USB-C to USB-C cable.

Launch the ROS2 node:

ros2 launch libsurvive_ros2 libsurvive_ros2.launch.py rosbridge:=true

Three topics are published:

• /libsurvive/cfg: listens for device configuration

• /libsurvive/imu: listens for devie inertial measurements

• /libsurvive/joy: listens to the button

We need to look at the topic /libsurvive/imu of type sensor_msgs/msg/Imu.

To display topic data in foxglove, we need first to add the topics /libsurvive/imu and /tf_static to the whitelist.

Annex: Connect the VIVE Tracker to a PC

This is simply the default method for connecting the unit. It can be used to ensure the device is working correctly. However for collecting data in ROS2, you will want to use the libsurvive library.

1- Download steam : https://store.steampowered.com/about/

2- Download steamVR https://store.steampowered.com/app/250820/SteamVR/

Connect the tracker to the PC via the USB-C cable then open Steam app. Got to "Library" then launch SteamVR app (click on the green button)

When launched, a small window will appear:

References:

[1] Official website

[2] Developer guide

[3] Borges, Miguel, Andrew Symington, Brian Coltin, Trey Smith, and Rodrigo Ventura. “HTC Vive: Analysis and Accuracy Improvement.” In 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2610–15. Madrid: IEEE, 2018. https://doi.org/10.1109/IROS.2018.8593707.

1. Introduction

2. Hardware setup

   1. prepare the 3D printed mount

   2. solder connectors and make cables

   3. balancing leads connection

   4. Setup validation - emulating a battery

3. Software setup in the BMS

4. Software setup in NavQP

5. References

Introduction

The RDDRONE-BMS772 is a standalone BMS reference design supporting 3 to 6 cell batteries.

The General Purpose MCU S32K144 provides great flexibility and communication to a PX4 based FMU via UAVCAN or I2C/SMBus. More information about the board can be found in references [1][2].

The BMS will be integrated in the system following the wiring diagram below:

Hardware setup

For setting up the hardware, we need:

• prepare the 3D printed mount

• solder connectors and make cables

• solder the balance leads and make its extension cable

• prepare a battery emulator setup

Prepare the 3D printed mount for the RDDRONE-BMS772 board

This particular 3D print will allow the RDDRONE-BMS772 to connect to the pre-production version of MR-B3RB lower chassis metal frame. Future versions may not need this adapter, or may be able to just use standoff's directly.

Solder connectors and make cables

We recommend pluggable cable connectors as shown below. Follow these images for guidance. Some XT60 connectors have a "back shell" to also help cover the solder joints. The backshell is preferable.

Balance leads connection

Because of the limited space on the B3RB. it is preferable to use a balancing leads connector that points upward. This will better clear the PDB that is adjacent to this board, and allow you to more easily plug in the battery's balancing cable later. Solder the white balance connector as shown below:

Balance leads extension cable

You will also need to make an extension cable for the balance leads connector. The leads that typically come as part of the battery is quite short. The suggested cable length is approximately 17cm.

Setup validation - emulating a battery

In this section we will prepare a setup to emulate the battery using a power supply. For this setup we need:

• 4 x 1kΩ resistors

• 2 wires: one black and one red

• Female balance leads connector with wires

Here are the steps:

1. Connect the female balance leads connector with wires and cut them to make them short.

2. Solder the resistors in series then solder two cables in both sides (black and red) as depicted in the picture above. Please make sure that the sides of the black and red wires are similar to the picture.

3. connect Black and red wires of the battery cells emulator to - and + input from the power supply.

4. Set the voltage in your power supply to 12V, then plug the input port to the power supply and the output port to the load that you are powering.

Software setup in the BMS

You can compile a binary from this GitHub repository: https://github.com/NXPHoverGames/RDDRONE-BMS772 or flash the existing binary https://github.com/NXPHoverGames/RDDRONE-BMS772/blob/main/Binary/nuttx.bin (follow these instructions).

Activate the cyphal can and setup the can id:

nsh> bms set can-mode cyphal
nsh> bms set cyphal-node-static-id 100
nsh> bms save
nsh> reboot

Software setup in NavQP

In this section, we present three methods to display received messages via CAN:

• using yakut CLI

• using pycyphal library

• using pycyphal library and ROS2

Prepare environment variables and DSDL namespace

Before the three next steps, you need to prepare the environment variables and add the DSDL namespace as follow:

mkdir -p ~/.cyphal
wget https://github.com/OpenCyphal/public_regulated_data_types/archive/refs/heads/master.zip -O dsdl.zip
unzip dsdl.zip -d ~/.cyphal
mv -f ~/.cyphal/public_regulated_data_types*/* ~/.cyphal

export UAVCAN__NODE__ID=42 
export UAVCAN__CAN__IFACE=socketcan:can0
export UAVCAN__CAN__MTU=8
export CYPHAL_PATH=/home/user/.cyphal

Using Yakut CLI

Yakút is a simple cross-platform command-line interface (CLI) tool for diagnostics and debugging of Cyphal networks. (For more information refer to [3])

The BMS772 software is already publishing three messages:

• type: reg.udral.physics.electricity.SourceTs_0_1, port: 4096

• type: reg.udral.service.battery.Status_0_2, port: 4097

• type: reg.udral.service.battery.Parameters_0_3, port: 4098

Print published Cyphal message in a terminal:

# yakut sub --with-metadata port:type
# Run the following commands in separate terminals

yakut sub --with-metadata 4096:reg.udral.physics.electricity.sourcets
yakut sub --with-metadata 4097:reg.udral.service.battery.status
yakut sub --with-metadata 4098:reg.udral.service.battery.parameters 

Using pycyphal library

First, clone the following repository:

git clone git@github.com:mounalbaccouch-nxp/BMS_cyphalcan.git

Run the script to print the received cyphal messages:

cd BMS_cyphalcan
python3.10 cyphal_bms_print_status.py

Using pycyphal library and ROS2

Clone the following repository:

git clone git@github.com:mounalbaccouch-nxp/BMS_cyphalcan.git

Run the ros2 node:

cd BMS_cyphalcan
python3.10 cyphal_bms_ros2-pub_status.py

Print the topic:

ros2 topic echo /battery_state

Once the topic is publishing battery state messages, we can display it in Foxglove. Fist add the topic to the while listed topics in robot.launch.py file

In your PC, download the following layout file and add it to Foxglove studio:

You should see two different tabs: one tab General for displaying the B3RB topics and one tab Battery for displaying the battery status raw data:

References

[1] BMS gitbook: https://nxp.gitbook.io/rddrone-bms772/software-guide-px4/introduction

[2] https://www.nxp.com/design/design-center/designs/smart-battery-management-for-mobile-robotics:RDDRONE-BMS772

[3] https://github.com/OpenCyphal/yakut

INTRODUCTION

The B3RB can use a TOF distance sensor as a cliff detector and the appropriate software to prevent it from driving off a table, down a stairway or any other "cliff" it may encounter while moving forward. These sensors could also be used pointing in other directions for other proximity detection applications. This tutorial describes how to perform cliff detection on MR-B3RB using TOF VL53L4CD sensor with MR-CANHUBK344 and MR-CANHUBK3-ADAP boards. The example and configuration shown below is with the MR-CANHUBK344 running Zephyr and Cognipilot but is showing the board outside of the installation on a MR-B3RB. When used with a B3RB, the power is supplied in the normal fashion and not with external connectors shown.

Operation Explanation

The Time of Flight VL53L4CD sensor measures distance within the range 1 mm to 1300 mm.

The sample application "samples/sensor/vl53l4cd" polls on the sensor every 1 second and reads the current distance measured from the device. Then it prints the distance on the console (in meters).

ITEMS REQUIRED

SETUP DIAGRAMS

HARDWARE SETUP

This hardware setup shows these boards outside of MR-B3RB on a tabletop. This of course can also be done on the vehicle itself. Simply plug in the sensor and the STEMMA QT cable to the CANHUB-ADAP. The power and other connections do not change from a normal MR-B3RB configuration.

1. Connect hardware components as shown in the block diagram above. The CANHUB-ADAP includes a I2C connector that follows the ADAFRUIT STEMMAQT standard.

2. Attach the MR-CANHUBK3-ADAP board on top of MR-CANHUBK344.

3. Power on the MR-CANHUBK344 board - connect the SYP connector to the MR-CANHUBK344, and the other end of the cable to your bench power supply or any source that could provide 5V DC.

SOFTWARE SETUP

Setup West Workspace

cd ~
west init -m "https://github.com/NXPHoverGames/zephyr.git" cliff_detection_project

cd ~/cliff_detection_project
west update

Building and Flashing

cd ~/cliff_detection_project/zephyr
git checkout tof_vl53l4cd_with_mux_pr

west build -b mr_canhubk3 samples/sensor/vl53l4cd -p
west flash

RESULTS

Get the shell of MR-CANHUBK344.

sudo chmod 666 /dev/ttyUSBn
cu -l /dev/ttyUSBn -s 115200

The shell should display output as:

proximity = 1
distance = 0.019 m
proximity = 1
distance = 0.021 m
proximity = 1
distance = 0.019 m
proximity = 1
distance = 0.018 m
proximity = 1
distance = 0.020 m
proximity = 1
distance = 0.017 m
proximity = 1
distance = 0.018 m
proximity = 1
distance = 0.019 m
proximity = 1
distance = 0.020 m
proximity = 1
distance = 0.018 m
proximity = 1
distance = 0.020 m
proximity = 1
distance = 0.018 m
proximity = 1
distance = 0.020 m
proximity = 1
distance = 0.020 m
proximity = 1
distance = 0.019 m
proximity = 1
distance = 0.016 m

1. What is a ToF camera

2. PMD Flexx camera specification

3. Install Royale SDK

4. Connect the camera to a PC

   1. Using Linux machine

   2. Using Windows machine

5. Connect the camera to the NavQP

   1. Dispaly via TCP server

   2. Display via RVIZ and ROS2

6. References

What is a ToF camera

A Time-of-Flight camera (ToF) is a range imaging sensor that produces a depth image, each pixel of which encodes the distance to the corresponding point in the scene [1].

In addition to the camera that produces 2D images, the ToF sensor includes an IR transmitter. By measuring the phase difference between the radiated (red) and reflected (blue) IR waves, we can calculate the distance to the object as depicted in the figure below.

PMD Flexx2 camera specification

The PMD Flexx2 camera intended use are: augmented Reality / Virtual Reality and SLAM. It has the following specifications:

• Depth Measurements from 10 cm to 7 m

• VCSEL with 940 nm Wavelength

• 38,000 3D Pixels with up to 60 FPS

• Independent of External Light Source

• 224 x 172 Resolution

• Multiple built-in User Modes

• 56 x 44 Degree Field-of-View

• USB 3.0 Type-C Port

• 71.9 x 19.2 x 10.6 mm compact size

• Software Suite "Royale" and API

Install Royale SDK

Download the royale SDK from the official website: https://pmdtec.com/en/download-sdk/

You need to fill in the form then you will get an email with a download link available for 24 hours. Use the password that comes with the camera.

You need to download two .zip files: one for your PC where you will display the camera data connected to the PC or the NavQP, and one for the NavQP.

The recent SDK for Flexx2 camera does not have the ROS2 driver. But the previous SDK does. Then, as recommendation, download the zip file libroyale-4.24.0.1201-LINUX-arm-64Bit-ub2004.zip for NavQP.

• Linux PC: libroyale-<ROYALE-SDK-VERSION>-LINUX-x86-64Bit.zip

• Windows PC: libroyale-<ROYALE-SDK-VERSION>-WINDOWS-x86-64Bit.exe.zip

• NavQP: libroyale-4.24.0.1201-LINUX-arm-64Bit-ub2004.zip

Connect the camera to a PC

Connect the camera to the PC using a USB-A to USB-C cable.

Using Linux machine

If you are using a Linux machine, download the zip file libroyale-<ROYALE-SDK-VERSION>-LINUX-x86-64Bit.zip from the download page, add the udev rules then run royaleviewer after reboot:

$ unzip ~/libroyale-<ROYALE-SDK-VERSION>-LINUX-x86-64Bit.zip
$ cd ~/libroyale-<ROYALE-SDK-VERSION>-LINUX-x86-64Bit/
$ sudo cp driver/udev/10-royale-ubuntu.rules /etc/udev/rules.d/
$ sudo udevadm control --reload-rules && sudo udevadm trigger (or reboot)
$ cd ~/libroyale-<ROYALE-SDK-VERSION>-LINUX-x86-64Bit/bin
$ ./royaleviewer

A GUI will start, click on start button on the bottom right corner to start the display:

You can use the TOOLS button to change some parameters. For example you can change the color range, or the type of data displayed (Gray image, depth image), etc

There is also a LOG button on the top right corner of the GUI where you can find useful debug or error logs.

Using Windows machine

If you are using a windows machine, install the zip file libroyale-<ROYALE-SDK-VERSION>-WINDOWS-x86-64Bit.exe. Unzip the file then run the executable to install the Royale Viewer.

Once installed you can find the executable with the name royaleviewer-royale_<ROYALE-SDK-VERSION> under C:\Users\<USER>\AppData\Roaming\Microsoft\Windows\Start Menu\Programs\royale_<ROYALE-SDK-VERSION> (Win64)

Once the program is launched, the steps are similar to those described in Linux sub-section.

Connect the camera to the NavQPlus

Connect the camera to the NavQPlus with an USB-C to USB-C cable (see picture below).

Before using the camera, you need to add the udev rules available in the SDK zip file that you downloaded from PMD download link.

$ unzip ~/libroyale-4.24.0.1201-LINUX-arm-64Bit-ub2004.zip
$ cd ~/libroyale-4.24.0.1201-LINUX-arm-64Bit/
$ sudo cp driver/udev/10-royale-ubuntu.rules /etc/udev/rules.d/
$ sudo udevadm control --reload-rules && sudo udevadm trigger (or reboot)

Display via TCP server

Under the bin/ directory, run the binary tcpserver:

$ cd  ~/libroyale-4.24.0.1201-LINUX-arm-64Bit/bin
$ ./tcpserver

Display via RVIZ and ROS2

The Royale SDK provides some sample codes available under samples/cpp/ directory. You should find a directory sampleROS2, which contains code for ROS2 driver.

You need to adjust this code to be able to compile in ROS2 Humble. First create a ROS2 workspace and copy the ROS2 driver there:

$ mkdir -p ws_tof/src
$ cp -rf ~/libroyale-4.24.0.1201-LINUX-arm-64Bit/samples/cpp/sampleROS2 ~/ws_tof/src

Then change the CMakeLists.txt file and the package.xml file to add the package pluginlib dependency:

Then compile the ROS2 workspace using the following command:

$ colcon build --cmake-args "-DCMAKE_PREFIX_PATH=~/libroyale-4.24.0.1201-LINUX-arm-64Bit/share"

Change the path to Royale SDK depending on your environment, and make sure to reference to share/ directory in this command.

Run the ROS2 node:

$ source install/setup.bash
$ ros2 run royale_in_ros2 royale_in_ros2

Make sure that mlan0 interface in listed in the list of interfaces in CycloneDDSConfig.xml file, then run RVIZ in a PC:

References:

[1] Hansard, Miles, Seungkyu Lee, Ouk Choi, and Radu Horaud. Time-of-Flight Cameras: Principles, Methods and Applications. SpringerBriefs in Computer Science. London: Springer London, 2013. https://doi.org/10.1007/978-1-4471-4658-2.

[2] https://3d.pmdtec.com/en/3d-cameras/flexx2/

[3] SDK download link: https://pmdtec.com/en/download-sdk/

There is an additional B3RB gitbook supporting the NXP AIM CHALLENGE (2024) where the B3RB is configured to use vision to drive around a track and avoid several obstacles. The simulation setup may be of interest to others and can be found here:

There is an opening in the rear plastic which can accept antennas from telemetry radios and other types of antennas. Changing the WiFi/BT antenna on NavQPlus may result in improved range. However it should be noted that this may cause your B3RB to no longer be compliant with FCC or CE regulations. It is your responsibility to know if you are compliant. The NavQPlus is tested and compliant only when used with the antenna provided when shipped.

Specifications: Gain: 8dBi Frequency Range: Dual Band WiFi 2.4GHz 5.8GHz VSWR: <2.0; Polarization: Linear Vertical; Impedance: 50 ohm; Direction: Omni-directional; Connector: RP-SMA Male Connector; Antenna Dimension: 16cm x 1.5cm Diameter; Net Weight: 62g; Operating Temperature: -20°С ~ +80°С Sto...

A low cost 20A power switch can be added inline to the battery power cable in order to turn the whole unit off without having to remove the battery. A 3D printed bracket was designed to attach to the underside of the main plate, and stick out the front of the B3RB under the front headlights.

This provides a clip/mount for the battery extension cable mount which attaches to the front standoff from the body to the frame.