Motion Planning for a Redundant Manipulator Using Genetic Algorithm

Abstract

The trajectory planning of redundant manipulator is key areas of research, which require efficient optimization algorithms. This paper presents a new method that combines multiple objectives for trajectory planning and generation for redundant manipulators. The algorithm combines collision detection, finding target and optimizing trajectory using Genetic algorithm. In order to optimize the path, an evaluation function is defined based on multiple criteria, including the total displacement of the end-effector, the total angular displacement of all the joints, as well as the uniformity of Cartesian and joint space velocities. These criteria result in minimized, smooth end-effector motions. These algorithm yields solutions instantaneously and generate the path. The proposed algorithm is analyzed and its performance is demonstrated through simulation and the results are compared with the other methods.