Methodology of concept control synthesis to avoid unmoving and moving obstacles (II)
Dynamic path generation problem of robot in environment with other unmoving and moving objects is considered. Generally, the problem is known in literature as find path or robot motion planning. In this paper we apply the behavioral cloning approach to design the robot controller. In behavioral cloning, the system learns from control traces of a human operator. The task for the given problem is to find a controller not only in the form of the explicit mathematical expression. So RBF neural network is used also. The goal is to apply controller for the mobile robot motion planning in situation with infinite number of obstacles. The advantage of this approach lies in the fact that a complete path can be defined off-line, without using sophisticated symbolical models of obstacles.
robot motion planning behavioral cloning rbf neural network cloning success linear regression machine learning obstacle avoiding