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Learn Robotics Programming

You're reading from   Learn Robotics Programming Build and control AI-enabled autonomous robots using the Raspberry Pi and Python

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Product type Paperback
Published in Feb 2021
Publisher Packt
ISBN-13 9781839218804
Length 602 pages
Edition 2nd Edition
Languages
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Author (1):
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Danny Staple Danny Staple
Author Profile Icon Danny Staple
Danny Staple
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Table of Contents (25) Chapters Close

Preface 1. Section 1: The Basics – Preparing for Robotics
2. Chapter 1: Introduction to Robotics FREE CHAPTER 3. Chapter 2: Exploring Robot Building Blocks – Code and Electronics 4. Chapter 3: Exploring the Raspberry Pi 5. Chapter 4: Preparing a Headless Raspberry Pi for a Robot 6. Chapter 5: Backing Up the Code with Git and SD Card Copies 7. Section 2: Building an Autonomous Robot – Connecting Sensors and Motors to a Raspberry Pi
8. Chapter 6: Building Robot Basics – Wheels, Power, and Wiring 9. Chapter 7: Drive and Turn – Moving Motors with Python 10. Chapter 8: Programming Distance Sensors with Python 11. Chapter 9: Programming RGB Strips in Python 12. Chapter 10: Using Python to Control Servo Motors 13. Chapter 11: Programming Encoders with Python 14. Chapter 12: IMU Programming with Python 15. Section 3: Hearing and Seeing – Giving a Robot Intelligent Sensors
16. Chapter 13: Robot Vision – Using a Pi Camera and OpenCV 17. Chapter 14: Line-Following with a Camera in Python 18. Chapter 15: Voice Communication with a Robot Using Mycroft 19. Chapter 16: Diving Deeper with the IMU 20. Chapter 17: Controlling the Robot with a Phone and Python 21. Section 4: Taking Robotics Further
22. Chapter 18: Taking Your Robot Programming Skills Further 23. Chapter 19: Planning Your Next Robot Project – Putting It All Together 24. Other Books You May Enjoy

Driving a robot from IMU data

In previous chapters, we saw how to use the PID algorithm, and in this chapter, how to detect a pitch, roll, and yaw from a magnetometer. Our robot can't move its pitch or roll, but it can change its heading.

In this demonstration, we'll get the robot to stay on course—to try to track North regardless of where we turn it. Let's see how. Have a look at the following diagram:

Figure 16.19 – Drive to heading behavior

Figure 16.19 shows the flow of data. The left of the diagram starts with a measured heading, and a heading setpoint going into a PID—the error value will be the difference between the two. The measured heading has come from the IMU + Fusion algorithm. We use the PID output to drive the motors so that they move at a fixed speed plus or minus the value, so the robot will turn to reduce the error. The robot moving will feed back into the IMU + Fusion algorithm, looping through...

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