The Gitbook documentation is updated regularly. Supportive feedback is welcome: iain.galloway@nxp.com

Welcome to the MR-B3RB Guide

We hope you are ready to embark on an exciting journey into the world of robotics. Meet MR-B3RB – your very own robot Buggy that you build from the ground up. Even though the the B3RB is toy sized, it represents a complete generic representation of a heterogeneous ROS2 enabled robotic platform with real time processors and model predictive real time control. This guide will walk you through the steps to prepare the hardware and the starter software. Please note this is an ADVANCED system, and a background in, or desire to learn ROS2, Linux, and Real Time Operating Systems is a pre-requisite in order to be successful in further development on the platform.

What is MR-B3RB?

MR-B3RB stands for "Mobile Robotics - Buggy 3 Revision B." It's a mobile robotics platform designed to ignite your curiosity and expand your understanding of robotics, programming, and engineering.

MR-B3RB-Mhas the following features:

• Embedded Linux Computer

  • Running Ubuntu POC and ROS2

  • Wireless Connectivity

  • CAN Bus

  • T1 two wire Ethernet and "regular" Ethernet

  • UARTs and other IO

• Real time Microprocessor running

  • Zephyr RTOS

  • Cognipilot for

    • Hosting state of the art Model Predictive Control real time control system

    • and framework for transparent sensor and actuator communications to ROS

  • T1 Ethernet

  • CAN connectivity

  • UART/SPI/I2C/PWMS, LED lighting and other hardware controls.

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.

Let's get started on this exciting adventure and bring your MR-B3RB to life!

Upper and Lower Chassis

Here we distinguish between the B3RBs lower & upper chassis:

Lidar Arch

This is the assembled buggy minus the top cover. The "bridge" with the lidar module may be referred to as the top plate, the top arch, Lidar arch or the lidar plate:

You will notice that throughout this guide, we use these names. At least now you know what we mean by it.

There are a variety of NXP Mobile Robotics enablements that each have their own GitBook doc as well as reference and product pages on NXP.com. You may want to review some of these other GitBooks to find more detail about specific boards used in the B3RB or boards which could interface with the B3RB:

• : Quick reference and index for all our mobile robotics solutions.

• NavQPlus: i.MX 8M Plus companion computer for mobile robotics

• MR-B3RB: NXP Buggy3 Rev B platform using NavQPlus and MR-CANHUBK344

• : The orginal Drone competition with links to Drone & rover dev. kits, with FMUK66 vehicle management unit, and now the MR-VMU-RT1176 vehicle management unit.

• : Autonomous model car competition for students.

• : Small form factor CAN-FD to 100BASE-T1 ethernet bridge.

• : CAN-FD node for mobile robotics applications.

• RDDRONE-BMS772: Battery management system (3-6 cells).

• RDDRONE-T1ADAPT: 100BASE-T1 ethernet adapter.

ROS2+Cognipilot Complexity

While anyone can build the MR-B3RB, and get it to perform the basic function as described here, further meaningful development will at minimum require some knowledge of ROS2. Below are some suggested training websites to learn about ROS2. Fundamentally B3RB is designed to be a Linux based ROS2 based robotic system with an attached real time control microcontroller. The default configuration uses Ubuntu Linux to run ROS2, as well as Zephyr RTOS + Cognipilot. Cognipilot provides the infrastructure in Zephyr to provide transparent and efficient communications to ROS2, Manage Sensors and Actuators in real time, and host the actual control system algorithms for the vehicle. Even more involved is the development of control algorithms themselves. You do NOT need to become a controls theory expert to use B3RB or any of the other pre-configured vehicle models in Cognipilot, but be aware of the following: The control algorithm software is developed externally, synthesized and then hosted by Cognipilot which is a key feature of Cognipilot Cerebri module. Control Algorithms can be simple or state of the art Model Predictive Control (MPC). Currently B3RB uses modern Lie group MPC theory. Refer to the for more details on this if you are interested in diving deeper. Note also that the same MR-B3RB hardware *can* support any other Linux or RTOS software, but in this GitBook the configuration of ROS2 + Zephyr is the focus robotics enablement.

Suggested ROS2 study resources

ROS2 is an entire subject to study on it's own. In order to be successful in further development, it is strongly suggested you spend some time studying ROS2 fundamentals. There are many resources publicly available for this. Below are only a few.

ROS2 Fundamentals

Udemy or other types or courses provide "completion certificates" a few examples are:

NAV2 module in ROS2 training

To learn about how to run a the robots you will want to take:

Udemy ROS2 NAV2

The Construct - ROS2 NAV2 Navigation

ROSCON

ROSCON is an highly recommended in-person conference and a great way to jumpstart your understanding of the latest development in ROS2. If you have the opportunity to attend it is an excellent conference experience.

B3RB specific abbreviations/glossary

Ackermann Steering:

A geometrical arrangement in vehicles ensuring all wheels follow concentric circular paths while turning, allowing inner wheels to turn sharper than outer wheels, thus reducing tire slip and wear. The B3RB uses Ackermann steering geometry.

CAN Bus

Controller Area Network Bus: A robust vehicle bus standard designed to allow microcontrollers and devices to communicate with each other without a host computer. The NavQPlus and the MR-CANHUBK344 both have CAN bus ports. By default nothing is attached, but you could attach things like Servos, motor controllers, GPS if they had a CAN bus interfaec. The MR-UCANS32K1SIC is a small board that would allow for development of CAN peripherals.

CogniPilot:

The software platform used in MR-B3RB to enable autonomous navigation and control, integrating sensor data and executing navigation algorithms.

GPS

(Global Positioning System): A satellite-based navigation system used in MR-B3RB to provide accurate position and timing information.

IMU

(Inertial Measurement Unit): A device that measures and reports a robot's specific force, angular rate, and sometimes the magnetic field surrounding the body, aiding in navigation and orientation.

Kalman Filter: An algorithm that uses a series of measurements observed over time, containing statistical noise and other inaccuracies, to produce estimates of unknown variables that tend to be more accurate than those based on a single measurement alone.

LIDAR: Light Detection and Ranging, a remote sensing method used in MR-B3RB for measuring distances and creating detailed maps of the environment.

MR-CANHUBK344: A central hub in the MR-B3RB system used for managing CAN (Controller Area Network) communications between different modules.

NavQPlus: A development platform used in MR-B3RB for advanced computing and sensor integration, including cameras and GPS. PWM (Pulse Width Modulation): A technique used to control the power supplied to electrical devices, crucial for motor speed control in MR-B3RB.

QDEC (Quadrature Decoder): A system used to interpret signals from rotary encoders, providing precise measurements of wheel rotations in MR-B3RB.

RGB LED: A light-emitting diode that can emit red, green, and blue colors, used in MR-B3RB for visual status indicators.

ROS2 (Robot Operating System 2): An open-source framework for robot software development, providing tools and libraries for building and controlling robots like MR-B3RB.

SLAM (Simultaneous Localization and Mapping): A process by which a robot or device constructs a map of an unknown environment while simultaneously keeping track of its location within that environment.

ToF (Time of Flight) Camera: A depth sensor that measures the time it takes for a light signal to return after being reflected off an object, used in MR-B3RB for obstacle detection.

General Robotics Glossary Autonomy vs Automation

- Automation: Derived from the Greek word "automaton," meaning something that acts by itself. Refers to machines repeating the same motion or tasks without human intervention.

- Autonomy: The capability of a system to govern itself and make decisions independently, operating under its own set of laws.

Robot vs Vehicle

- Robot: From the Czech word "robota," meaning forced labor. A machine that operates automatically or via remote control to perform tasks.

- Vehicle: A device designed for transporting people or cargo. (Despite this, the B3RB may still commonly be referred to as a type of vehicle)

Robotic System: A combination of a robot, its environment, supporting infrastructure, other machines, and humans interacting with it.

AMR vs AGV

- AMR: Autonomous Mobile Robot, capable of navigating and making decisions independently.

- AGV: Automated Guided Vehicle, follows predefined paths or instructions.

Agent and World vs Controller and Plant

- Agent and World: Conceptual framework where the agent (robot) interacts with the world (environment).

- Controller and Plant: The controller directs the plant (mechanical system) to achieve desired outcomes.

Estimate and Belief

- Estimation: The process of transforming sensor data into actionable information such as position, orientation, and velocity for the robot.

- Belief: The robot's internal representation or estimate of its current state based on the processed data.

PID Controller (Proportional-Integral-Derivative Controller): A control loop mechanism used in industrial control systems, employing feedback to maintain the desired output of a system.

Waypoint Navigation: A navigation method in which a robot or vehicle follows a series of pre-defined points, or waypoints, to reach its destination.

This guide is designed to help you quickly understand and effectively use the MR-B3RB platform. Whether you're a beginner or an experienced developer, you can tailor your experience by following the structure below:

1. For Beginners:

If you're new to the MR-B3RB platform or its components, we recommend starting from the beginning and working your way through each section in order. The guide is organized sequentially, with foundational concepts explained first, followed by advanced topics.

Are you unfamiliar with some of the NXP systems? Please check out the section Learn more about the NXP Mobile Robotics enablement to learn more about the variety of compatible robotics boards.

2. For Advanced Users (Topic-Specific Exploration):

Experienced users looking for specific information can jump directly to the section they need. Each section is designed to be self-contained, so you can explore topics independently without needing to read the entire guide.

3. Code Examples and Exercises:

Throughout the guide, you'll find code snippets, examples, and exercises. These are marked clearly and are essential for hands-on learning. We encourage you to replicate and experiment with these examples to deepen your understanding.

4. Notes, Tips, and Warnings:

Look out for highlighted notes, tips, and warnings. These callouts contain critical information, best practices, and potential pitfalls that can save you time and effort.

5. External resources:

Some sections include links to external resources, interactive diagrams, or tools. These are designed to enhance your learning experience, so don’t hesitate to explore them for additional context.