This project is a collaboration with research groups at Penn (Mark Yim, Daniel Koditschek, Douglas Jerolmack) and at USC (Feifei Qian). The aim for this project is to develop methods for teams of robots to jointly overcome environmental hazards on the Moon by attaching to each other to form larger and more stable, maneuverable structures. The robots will use their interactions with the ground to form a map of safe and risky terrain, attach to each other as support when the ground traversal risk is high, move in a coordinated fashion once joined, and, once the maneuver has been successfully completed, separate to continue their original individual missions.

The TRUSSES project will develop algorithms that provide robots with two main capabilities: 1) estimate robot-to-regolith interactions in order to plan safe maneuvers, and 2) plan truss formations and coordinated motions for robots to push and pull each other to safe locations. The system will be evaluated to verify risk estimation, risk avoidance, risk mitigation, and recovery from failure.

Our group primarily develops planning and localization methods for coordinated, risk-aware maneuvers in heterogeneous teams of ground robots operating with a partially known map. This map is built proprioceptively by an exploring quadruped and encodes spatial parameters for a robot-ground interaction model, enabling force prediction. It can also be transformed into a risk map that reflects uncertainty (unexplored regions) and poor terrain (where robots may get stuck). Heterogeneity is advantageous, as each robot interacts differently with the terrain, offering unique capabilities in team operations. This diversity requires high-level planning to assign roles aligned with each robot’s strengths, producing team configurations that support the rescue mission while avoiding high-risk zones. Once a target configuration is defined, robots reposition themselves using a reactive navigation planner and form truss connections. A truss-planner then computes joint motions so the connected network can move collectively to safer areas, where the robots can disconnect and resume individual tasks like exploration or transport.

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Acknowledgments

The work is supported by Lunar Surface Technology Research grant #80NSSC24K0127 from NASA’s Space Technology Research Grants Program. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of this organization.