Research On Motion Planning Approach For Redundant Space Manipulator

With the development of aerospace science and technology,space exploration becomes more and more.The appearance of space on-orbit service has accelerated the pace of space exploration.The space manipulator has become an important part for completing the space on-orbit service.It performs tasks alone or assists astronauts in space.It not only improves the efficiency of space exploration and development,but also reduces the economic costs of space operations.In complex and harsh space environment,the redundant space manipulator has the advantage of high efficiency for completing on-orbit service.Therefore,it is a great significance to study the redundant space manipulator for the development of aerospace industry.We analyze and study the motion planning approach for redundant space manipulator in this paper,aiming to provide a framework and method for solving related technical problems.The research is introduced in detail as the following four aspects:(1)To meet the requirements of space on-orbit service,a design method based on the concept of golden section is proposed.The joint coordinate system of redundant space manipulator is described by the Denavit-Hartenberg(D-H)parameter method,and then the kinematic model is established.The forward kinematics equations are derived by means of the transformation matrix.The analysis of workspace is implemented by Monte Carlo method,which verifies the rationality of model building method in this paper.(2)Aiming at reducing the economic costs of space on-orbit service,we proposed a trajectory planning method based on the hybrid parasitic particle swarm optimization(HPSO)algorithm to solve the trajectory planning problem on minimizing attitude disturbance for the free-floating redundant space manipulator.The mathematical equations are derived by the combination of kinematics equation and generalized Jacobian matrix.The joint angle is parameterized and the base attitude is expressed by the Euler parameter method.The objective function about minimizing base attitude disturbance is described.The parameters of objective function are optimized by the HPSO algorithm.Compared with the particle swarm optimization(PSO)algorithm and linear-weight particle swarm optimization(LWPSO)algorithm,the simulation results show that the proposed trajectory planning method can better solve the problem and have the advantage of high accuracy.(3)From the point view of security of space on-orbit service,the problem on obstacle avoidance path planning of redundant space manipulator is studied.An obstacle avoidance path planning method based on the symbiotic multi-swarm particle swarm optimization(SMPSO)algorithm is presented.First of all,the obstacles and links are modeled by the envelope method.The collision avoidance conditions between them are analyzed.Secondly,the fitness function is established.Finally,the obstacle avoidance path is planned by the SMPSO algorithm.The simulation results show that the proposed method is more effective and robust in solving the obstacle avoidance path planning problem of redundant space manipulator.(4)Considering the economy and safety of space on-orbit service,the problem on multi-objective motion planning of redundant space manipulator is analyzed and studied.A pyramidal segmentation-chaotic optimization multi-objective motion planning method is presented.The multi-objective motion planning function is established using the physical programming method combined with linear weighting method.Then,to solve the multi-objective planning function,a pyramid segmentation-chaotic optimization algorithm is proposed for hierarchical solving.Finally,the collision-free path sets are searched by the improved chaotic particle swarm(ICPSO)algorithm.The optimal path is also obtained by the ICPSO algorithm.Compared with other methods,the simulation results show that the proposed method has the advantage of faster speed and higher accuracy in solving the multi-objective motion planning problem of redundant space manipulator.