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Encoder-Based Localisation with Python
A smart robot can use its sensors with intelligent algorithms to guess its position in a known space, improving its guess as it gathers more information about its movements within that space.
In this chapter, we will see how to build this simple kind of artificial intelligence, making many guesses about where it is with its own mental model. The robot will update these guesses about where it is when it moves, using each movement to make more informed guesses about its position.
For the robot to navigate a space, it needs a mathematical model. We will see how to build and display this model. Then we will look at how to model the robot moving in that space.
We will then see how to refine the guesses and predictions into better predictions.
In this chapter, you will learn about the following topics:
- Representing and displaying the robot as poses
- Modeling a test area
- Moving poses with encoders
- Localisation debugging tools
- Refining pose probabilities...
