基于图的空间站多肢体舱内机器人路径与立足点同步规划
Graph-Based Simultaneous Path and Foothold Planning for Multi-Limbed Intra-Vehicular Robots in Space Stations
查看机构详情
- Tohoku University（东北大学）
- New Industry Creation Hatchery Center (NICHe), Tohoku University（东北大学新产业创造孵化中心）
机构由 AI 辅助整理，请以论文原文为准。
浏览论文内容
中文总结 AI 辅助
针对空间站多肢体舱内机器人，提出基于图论的路径与立足点同步规划框架，在满足可操作性约束下高效搜索可行站立序列，并经ISS舱体三维仿真验证其可行性与高效性。
中文摘要 AI 辅助
在空间站中，机器人辅助操作对于减轻宇航员工作负担和提高在轨活动效率至关重要。配备抓取末端执行器的多肢体舱内机器人（MLIVRs）已成为一种有前景的解决方案，因为它们能够牢固地抓取预先存在的接口，如扶手和座椅轨道，从而在微重力环境中实现稳定移动和强力操作。由于这些接口上可抓取的位置在空间上有限且离散分布，MLIVRs的运动规划必须与立足点规划联合解决。本文提出了一种基于图论的MLIVRs路径与立足点同步规划框架。所提方法在满足可操作性约束的同时，高效搜索多肢体机器人的可行站立序列。通过在国际空间站（ISS）舱体的三维模型中进行仿真，验证了所提框架的有效性，展示了其在真实舱内环境中生成可行且高效移动计划的能力。
英文摘要
Robot-aided operations in space stations are essential for reducing the workload of astronauts and improving the efficiency of on-orbit activities. Multi-limbed intra-vehicular robots (MLIVRs) equipped with grappling end-effectors have emerged as a promising solution, as they can securely grasp pre-existing interfaces, such as handrails and seat tracks, thereby enabling stable locomotion and forceful manipulation in microgravity environments. Since graspable locations on these interfaces are spatially limited and discretely distributed, motion planning for MLIVRs must be addressed jointly with foothold planning. This paper presents a simultaneous path and foothold planning framework based on graph theory for MLIVRs. The proposed method efficiently searches for feasible stance sequences for a multi-limbed robot while satisfying manipulability constraints. The effectiveness of the proposed framework is validated through simulations in a 3D model of the International Space Station (ISS) cabin, demonstrating its capability to generate feasible and efficient locomotion plans in realistic intra-vehicular environments.
