In context
As space agencies and commercial operators move toward building large structures in orbit—such as space stations and large communication satellites—the need for autonomous robotic assembly has grown. Motion planning is a critical bottleneck, especially in crowded, narrow environments where traditional sampling-based planners struggle. This 2023 study from Northwestern Polytechnical University addresses that challenge with a hybrid sampling approach tailored for space manipulators.
What was reported
Researchers proposed the HS-RRV (hybrid sampling rapidly-exploring random vine) algorithm to improve motion planning efficiency for space manipulators during on-orbit assembly in cluttered environments. The method simultaneously samples in both workspace and configuration space, with sampling weights dynamically adjusted during the process. This balances algorithm completeness with efficient use of workspace information to narrow the search.
The local planner employs hierarchical quadratic least-square programming (HQLP), incorporating kinematic and dynamic constraints to enhance trajectory executability. When the algorithm encounters complex regions, it uses bridge tests and principal component analysis to identify local space types and determine more effective expansion directions.
Simulations across multiple assembly scenarios showed that HS-RRV outperformed existing methods in computation efficiency, planning success rate, and trajectory length.
Why it mattered
This work advances autonomous on-orbit assembly by making motion planning more reliable in the tight, obstacle-rich spaces typical of assembly tasks. The hybrid sampling strategy offers a practical path to improve both speed and robustness, which is essential for future large-scale space construction and maintenance missions.
"The results show that the proposed method has higher computation efficiency and planning success rate, as well as a relatively shorter trajectory length."
Source: 《机器人》期刊 (robot.sia.cn) · Published 2023-03-11 · “基于HS-RRV算法的空间机械臂在轨装配运动规划”