Book Image

Robotics at Home with Raspberry Pi Pico

By : Danny Staple
Book Image

Robotics at Home with Raspberry Pi Pico

By: Danny Staple

Overview of this book

The field of robotics is expanding, and this is the perfect time to learn how to create robots at home for different purposes. This book will help you take your first steps in planning, building, and programming a robot with Raspberry Pi Pico, an impressive controller bursting with I/O capabilities. After a quick tour of Pico, you’ll begin designing a robot chassis in 3D CAD. With easy-to-follow instructions, shopping lists, and plans, you’ll start building the robot. Further, you’ll add simple sensors and outputs to extend the robot, reinforce your design skills, and build your knowledge in programming with CircuitPython. You’ll also learn about interactions with electronics, standard robotics algorithms, and the discipline and process for building robots. Moving forward, you’ll learn how to add more complicated sensors and robotic behaviors, with increasing complexity levels, giving you hands-on experience. You’ll learn about Raspberry Pi Pico’s excellent features, such as PIO, adding capabilities such as avoiding walls, detecting movement, and compass headings. You’ll combine these with Bluetooth BLE for seeing sensor data and remotely controlling your robot with a smartphone. Finally, you’ll program the robot to find its location in an arena. By the end of this book, you’ll have built a robot at home, and be well equipped to build more with different levels of complexity.
Table of Contents (20 chapters)
1
Part 1: The Basics – Preparing for Robotics with Raspberry Pi Pico
7
Part 2: Interfacing Raspberry Pi Pico with Simple Sensors and Outputs
12
Part 3: Adding More Robotic Behaviors to Raspberry Pi Pico

Exercises

The following exercises will deepen your understanding of the topics discussed in this chapter and make the robot code better:

  • The IMU could be added by storing a previous state and calculating the delta. You could mix this into the rot1/rot2 values by taking the average of encoder calculations versus the IMU angles, or consider whether one sensor is more trusted than the others. You will need to calibrate the IMU before it can be used.
  • The robot’s pose guesses get stuck in local maxima – good but wrong guesses that are likely based on sensor positions. Consider throwing in 10 fresh guesses at every population to nudge the code to try other options.
  • We are using only two observations per pose – having more distance sensors could improve this but will make the model slower.
  • Could you add a target zone to the arena? Consider how PIDs could be used to steer the robot toward this. Perhaps feed the PID with the mean pose.
  • You can improve...