Path planning algorithm for space manipulator with a minimum energy demand
Wing Kwong Chung, Yangsheng Xu · 2012
This paper presents a methodology to plan a global path for the gaits of space manipulators with a minimum total energy demand. Different from conventional approaches, we propose the consideration of the motions composition for a manipulator to plan a path. For the path planning problem, it is first modeled as a Traveling Salesman Problem (TSP) and the optimization goal is to search a path with a minimum energy demand. After that, the individual energy demand of different gaits of a space manipulator is estimated and analyzed. To solve the optimization problem, conventional genetic algorithm (GA) is utilized. To enhance the performance of GA, we design and develop a novel genetic operator, called Planar-NN. It aims to search a solution path with more motion primitives which contribute a lower energy demand. To evaluate the performance of the proposed algorithm, numerous simulations are performed. Results show that it can search a path with the lowest total energy demand.