HQP-Based Obstacle Avoidance Motion Planning and Control of On-Orbit Redundant Manipulators

被引:0
|
作者
Xing, Hongjun [1 ]
Wang, Zeping [1 ]
Lei, Bin [1 ]
Xie, Yuyan [1 ]
Ding, Liang [2 ]
Chen, Jinbao [1 ]
机构
[1] Nanjing Univ Aeronaut & Astronaut, Natl Key Lab Aerosp Mech, Nanjing 210016, Peoples R China
[2] Harbin Inst Technol, State Key Lab Robot & Syst, Harbin 150001, Peoples R China
基金
中国国家自然科学基金;
关键词
On-orbit servicing; Redundant manipulator; Task prioritization; Hierarchical quadratic programming; Obstacle avoidance; RECURRENT NEURAL-NETWORKS; SPACE ROBOT; INVERSE KINEMATICS;
D O I
10.1007/s42405-025-00902-0
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
On-orbit redundant manipulators, owing to their flexibility and fault tolerance, are well-suited for performing tasks in confined environments. However, complex space environments introduce significant challenges in obstacle avoidance, motion planning, and control. This paper focuses on a seven-degree-of-freedom (7-DoF) manipulator of the space station remote manipulator system (SSRMS) type, addressing its kinematics and obstacle avoidance in motion planning and control. Initially, a 3D model of the redundant manipulator was developed, and its forward kinematics were established using the Denavit-Hartenberg (D-H) method. The Jacobian matrix was computed through the vector product method. Inverse kinematics were subsequently resolved using a redundancy resolution approach based on quadratic programming (QP), and a joint velocity-based motion planning strategy was designed to ensure high-precision end-effector trajectory tracking. Additionally, a configuration optimization function was introduced to address singularity avoidance and joint limit constraints using the gradient descent method. To prioritize tasks, dual-trajectory tracking was implemented using hierarchical quadratic programming (HQP), enabling the manipulator to effectively avoid obstacles. Finally, several simulations were conducted to validate the effectiveness of the proposed methods.
引用
收藏
页数:16
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