Journal of Astronautics ›› 2022, Vol. 43 ›› Issue (3): 366-373.doi: 10.3873/j.issn.1000-1328.2022.03.012

Previous Articles     Next Articles

Path Planning Method of Soft Landing for Multi Node Probe

WANG Xin, ZHAO Qing jie, YU Chong chong, ZHANG Chang chun, CHEN Yong quan   

  1. 1. School of Computer Science, Beijing Institute of Technology, Beijing 100081, China;
    2. School of Artificial Intelligence, Beijing Technology and Business University, Beijing 100048, China
  • Received:2021-04-29 Revised:2021-07-27 Online:2022-03-15 Published:2022-03-15

Abstract: The deep space probe with flexible connected multiple nodes is probably a solution to the possible overturn or rebound in single node probe landing on an asteroid. Therefore, we construct a probe with flexible connected three nodes, model the soft landing process, and propose a multi task deep reinforcement learning method with self attention mechanism. Each node’s state is described referring to the probe base. Furthermore, joint learning among nodes is used to improve their adaptability. At the same time, the self attention is applied to make the nodes focus on their own tasks and learn better strategies to obtain higher rewards for feature extraction of the probe and obstacles. Experimental results show that the method proposed in this paper is more beneficial to the stable landing of the probe compared with other methods.

Key words: Deep space probe, Soft landing, Deep reinforcement learning, Multi task learning, Self attention mechanism

CLC Number: