Graph-Based Simultaneous Path and Foothold Planning for Multi-Limbed Intra-Vehicular Robots in Space Stations

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.

Comments: Accepted at the International Conference on Space Robotics 2026 (iSpaRo 2026)