A Position–Velocity Hierarchical Command Cone Search Optimizer for Terminal Base Disturbance Minimized Planning of Free-Floating Space Manipulators
Free-floating space manipulators exhibit strong dynamic coupling between the robotic system and its spacecraft base, where configuration transitions may generate significant base-attitude disturbances. This paper proposes a constrained trajectory-planning framework using eighth-order Bézier curves, in which boundary conditions of position, velocity, and acceleration are analytically satisfied through endpoint control points, while intermediate control points are optimized under joint constraints. To solve the resulting nonlinear constrained optimization problem, a Position–Velocity Hierarchical Command Cone Search Optimizer (PV-HCCSO) is developed. The proposed optimizer integrates a hierarchical search architecture, representative-guided multi-region exploration, adaptive cone search, position–velocity cooperation, and stagnation-aware diversity-restoration mechanisms. Numerical simulations of a 7-DOF free-floating space manipulator demonstrate that the generated trajectories satisfy all kinematic constraints while effectively suppressing terminal base-attitude disturbances. Compared with WCA, PSO, and CPO, PV-HCCSO achieves reductions of 93.89%, 85.31%, and 81.96% in the mean final fitness value, respectively. Statistical analysis over 40 independent trials confirms significant performance improvements (F = 33.705, p < 0.001). Furthermore, evaluations on the 20-dimensional CEC2022 benchmark suite show superior optimization capability with an average rank of 1.28. The results demonstrate the effectiveness and robustness of PV-HCCSO for constrained trajectory planning of free-floating space manipulators.
Authors
- Shicai Shi
- ZhiQi Li
- Minghe Jin (ORCID: https://orcid.org/0000-0001-6643-2824)
- Hong Liu
- Jian Liu
Institutions
- Harbin Institute of Technology (CN)
- State Key Laboratory of Robotics and Systems (CN)
Publication Details
- Journal
- Aerospace
- Published
- 2026-11-06
- DOI
- https://doi.org/10.3390/aerospace13111032
- Primary Topic
- Metaheuristic Optimization Algorithms Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Ministry of Education of the People's Republic of China