TY - GEN
T1 - A Pose Synchronization Control Method for the Approach Phase of Lunar Lander
AU - Gao, Feng
AU - Zhong, Wei
AU - Li, Zhigang
AU - Jing, Wuxing
AU - Gao, Changsheng
N1 - Publisher Copyright:
© 2021 IEEE
PY - 2021
Y1 - 2021
N2 - Aiming at the problem of autonomous obstacle avoidance in the approach phase of lunar soft landing, a dynamic autonomous obstacle avoidance strategy of"open-loop first, closed-loop afterwards " is proposed in the accurate obstacle avoidance stage, and the pose synchronization control problem in the open-loop control stage of this strategy is studied First, establishing the dynamic model of the approach phase in the local coordinate system of the target point, and on this basis, describing the field-of-view constraint of the visual sensor, boundary conditions and performance index in the pose synchronization optimal control problem. Then based on the improved salp swarm algorithm (ISSA) and the compound penalty function, the global optimization of the pose synchronization optimal control problem is performed Finally, a variety of simulation examples are used to verify the performance of the proposed algorithm, and the simulation results show the effectiveness of the designed algorithm.
AB - Aiming at the problem of autonomous obstacle avoidance in the approach phase of lunar soft landing, a dynamic autonomous obstacle avoidance strategy of"open-loop first, closed-loop afterwards " is proposed in the accurate obstacle avoidance stage, and the pose synchronization control problem in the open-loop control stage of this strategy is studied First, establishing the dynamic model of the approach phase in the local coordinate system of the target point, and on this basis, describing the field-of-view constraint of the visual sensor, boundary conditions and performance index in the pose synchronization optimal control problem. Then based on the improved salp swarm algorithm (ISSA) and the compound penalty function, the global optimization of the pose synchronization optimal control problem is performed Finally, a variety of simulation examples are used to verify the performance of the proposed algorithm, and the simulation results show the effectiveness of the designed algorithm.
KW - approach phase
KW - autonomous obstacle avoidance
KW - improved salp swarm algorithm
KW - pose synchronization
UR - https://www.scopus.com/pages/publications/85128009495
U2 - 10.1109/CAC53003.2021.9728619
DO - 10.1109/CAC53003.2021.9728619
M3 - 会议稿件
AN - SCOPUS:85128009495
T3 - Proceeding - 2021 China Automation Congress, CAC 2021
SP - 8013
EP - 8018
BT - Proceeding - 2021 China Automation Congress, CAC 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 China Automation Congress, CAC 2021
Y2 - 22 October 2021 through 24 October 2021
ER -