Multiobjective preimpact trajectory planning of space manipulator for self-assembling a heavy payload

Abstract

To assemble a heavy payload to the spacecraft (free-floating base), the present study proposes a scheme of multiobjective trajectory planning for preimpact motion of redundant space manipulator (mounted on the base). Force impulse for self-assembly is derived as the function of joint angles/velocities, base pose, and impact direction. The trajectory planning problem is formulated as multiobjective optimization to minimize force impulse, base attitude disturbance, and energy consumption in the load-carrying process. A two-stage trajectory planning algorithm is proposed. To be specific, at the first stage, multiple desired configurations at the contact point are generated by position-level inverse kinematics with Newton–Raphson iterative method. At the second stage, joint trajectories satisfying joint angle limits and desired motion of the payload are parameterized by coefficients of sinusoidal polynomial functions. Multiobjective particle swarm optimization algorithm is adopted to solve the problem of multiobjective trajectory planning, and screening process is conducted to reserve nondominated solutions in limits of joint torques. The algorithm is implemented to a seven degrees of freedom space manipulator, and the effectiveness of the proposed method is verified by simulation results.

A Review of Spatial Robotic Arm Trajectory Planning

“…Xu et al [96] designed a trajectory planning algorithm in a cartesian coordinate system using the incomplete motion characteristics of the free-floating space robot system, combined with the particle swarm optimization algorithm to search for the optimal solution of the objective function and explored the trajectory planning problem of the space robotic arm in capturing the runaway spin satellite from the perspective of engineering practice. Liu et al [97] solved the multi-objective trajectory planning problem with the Newton-Raphson iterative method and multi-objective particle swarm optimization algorithm for the free-floating robotic arm model, respectively. Huang et al [98] used the PSO algorithm to search the global time-optimal trajectory of a spatial manipulator.…”

NA-OR: A path optimization method for manipulators via node attraction and obstacle repulsion

“…In the past few decades, manipulators have received considerable attention in industrial production and real-life applications, e.g., components assembling [1,2], workpieces welding [3,4], materials transporting [5,6], on-orbit servicing [7,8], and oropharyngeal swab sampling [9][10][11]. In the typical manipulating tasks, a feasible path between the predefined initial and terminal configurations should be generated, following which the manipulator can reach the desired configuration and avoid collisions with self-body as well as obstacles in the workspace [12].…”

FBi-RRT: a path planning algorithm for manipulators with heuristic node expansion

“…Over the past few decades, the manipulators have received increasing attention, due to their extensive applicability in civil and military fields, for example, medical sampling [1][2][3], on-orbit servicing [4][5][6], agricultural picking [7,8], nuclear facility maintenance [9,10], etc. In the path planning problem of manipulators, given the initial and terminal configurations, the manipulator is required to generate a feasible path (i.e., a sequence of configurations), following which the manipulator can reach the desired configuration with the consideration of avoiding self-collision and collision with environmental obstacles, also considering the object potentially attached to the end-effector [11].…”