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Constraint trajectory planning for redundant space robot

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Abstract

In this paper, we propose a novel hybrid heuristic algorithm, particle swarm optimization, and whale optimization algorithm (PSO–WOA), to solve a multi-objective optimization problem relating to point-to-point trajectory planning of space robots. First of all, the kinematics of the space robot is introduced, and the motion of each revolute joint of the manipulator is parameterized by Bézier curve. Then, contradictory objective functions are proposed, and the trajectory planning problem is transformed into a multi-objective optimization problem. The pose of the end-effector at the end of motion is set as the primary objective. The base disturbance, execution time, and manipulability of the end-effector are also taken into account. Furthermore, self-collision avoidance during the motion is also considered. The trajectory planning problem finally comes down to finding an optimal parameter of the Bézier curve for each joint. We propose a novel hybrid PSO–WOA, which is supposed to take advantages of the best of both methods: the exploration feature of the WOA and exploitation feature of the PSO. In order to enhance the performance of the PSO–WOA, the good point set and lévy flight stochastic steps are employed for the initialization and updating process, respectively. The proposed method is applied to generate an optimal trajectory for a redundant free-floating space robot. The simulation results demonstrate the effectiveness of the PSO–WOA.

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Data availability

The program code and datasets generated during and/or analyzed in the current study are available from the corresponding author on reasonable request.

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Acknowledgements

This work has been supported by the Science Center Program of National Natural Science Foundation of China under Grant No. 62188101, the National Natural Science Foundation of China (61833009, 61690212), and Heilongjiang Touyan Team.

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Authors and Affiliations

  1. School of Astronautics, Harbin Institute of Technology, Harbin, 150001, China

    Run Li & Ming Liu

  2. School of Computation, Information and Technology, Technical University of Munich, 80333, Munich, Germany

    Johannes Teutsch & Dirk Wollherr

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  1. Run Li
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Correspondence to Ming Liu.

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Li, R., Liu, M., Teutsch, J. et al. Constraint trajectory planning for redundant space robot. Neural Comput & Applic 35, 24243–24258 (2023). https://doi.org/10.1007/s00521-023-08972-5

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