Obstacle Avoidance of a Class of Underactuated Robot Manipulators: GA based approach
This paper presents a practical collision-free motion planning method for general underactuated robot manipulators. First the dynamic properties of underactuated robot manipulator are analyzed, and then the collision avoidance problem is formulated and solved as a position-based force control problem. Virtual generalized force representing the intrusion of the arm into the obstacle dangerous zone is computed in real time using a virtual spring-damper model. The partly stable controllers are adopted and the energy based fitness function is built, then the best switching sequence of partly stable controllers is obtained by genetic algorithm. Because the proposed method does not make any hypothesis about the degree of freedom, it can be used without modification for arms with a large number of degree of freedom. At last numerical simulations are carried out to illuminate the validity of the proposed method.
obstacle avoidance underactuated robots motion planning genetic algorithm