Optimal Path Planner for Mobile Robot in 2D Environment

The problem of path planning for the case of a mobile robot moving in an environment filled with obstacles with known shapes and positions is studied. A path planner based on the genetic algorithm approach, which generates optimal in length path is proposed. The population member paths are generated by another algorithm, which uses for description of the obstacles an artificial annealing neural network and is based on potential field approach. The resulting path is piecewise linear with changing directions at the corners of the obstacles. Because of this feature, the inverse kinematics problems in controlling differential drive robots are simply solved: to drive the robot to some goal pose (x, y, theta), the robot can be spun in place until it is aimed at (x, y), then driven forward until it is at (x, y), and then spun in place until the required goal orientatio