Long-Horizon Multi-Robot Rearrangement Planning for Construction Assembly
This addresses the challenge of efficient multi-robot coordination in construction assembly, enabling architects to optimize designs for robotic assembly, though it is incremental as it extends prior work on planning to larger teams.
The paper tackles the problem of planning for large, heterogeneous robot teams in construction assembly by developing a system that parallelizes complex task and motion planning, enabling cooperative manipulation with unknown arrival times. It demonstrates robustness over long horizons and scalability to many objects and agents, with real-world execution on two robot arms.
Robotic assembly planning enables architects to explicitly account for the assembly process during the design phase, and enables efficient building methods that profit from the robots' different capabilities. Previous work has addressed planning of robot assembly sequences and identifying the feasibility of architectural designs. This paper extends previous work by enabling planning with large, heterogeneous teams of robots. We present a planning system which enables parallelization of complex task and motion planning problems by iteratively solving smaller subproblems. Combining optimization methods to solve for manipulation constraints with a sampling-based bi-directional space-time path planner enables us to plan cooperative multi-robot manipulation with unknown arrival-times. Thus, our solver allows for completing subproblems and tasks with differing timescales and synchronizes them effectively. We demonstrate the approach on multiple case-studies to show the robustness over long planning horizons and scalability to many objects and agents of our algorithm. Finally, we also demonstrate the execution of the computed plans on two robot arms to showcase the feasibility in the real world.