Introducing robot path planning
In this section, we will be applying decision tree techniques to perform robot navigation. Some people like to refer to these as graph-based solutions, but any sort of navigation problem ends up being a decision tree. Consider as you drive your car, can you divide your navigation problems into a set of decisions – turn right, turn left, or go straight?
We are going to take what we have learned so far and press on to a problem related to classification, and that is grid searching and path finding. We will be learning about the famous and widely used A* (pronounced A-star) algorithm. This will start with grid navigation methods, topological path finding, such as GPS route finding, and finally, expert systems. You will see that these are all versions and variations on the topic of decision trees that we have already learned.
Some problems and datasets, particularly in robotics, lend themselves to a grid-based solution as a simplification of...
