Coordinated Multi-Robot Disassembly for Makespan Optimization of Large-Scale Assemblies

2026-08-06

AI Summary

This work addresses the challenge of prolonged makespan in multi-robot collaborative disassembly within confined spaces, where motion conflicts frequently occur. The authors propose CoMuDi, a novel approach that deeply integrates spatiotemporal RRT* (ST-RRT*) into multi-robot disassembly planning for the first time. CoMuDi models the assembly using a dependency graph to generate composite tasks, propagates temporal constraints to coordinate robot actions, and leverages ST-RRT* to optimize the execution time of individual tasks, thereby minimizing overall makespan. Evaluated across six benchmark scenarios involving up to 49 parts and nine robots, CoMuDi significantly improves planning success rates while effectively reducing both makespan and robot idle time.

Abstract

Multi-robot task and motion planning for disassembly tasks requires robots to operate in confined workspaces while coordinating their motions with other robots. To tackle this problem, we propose a planning method called coordinated multi-robot disassembly (CoMuDi). CoMuDi coordinates a team of robots for disassembly tasks. The input is a team of robots, an assembly of objects, and a dependency graph. Based on this information, we create compound tasks for pick, place, and exit motions. By propagating temporal constraints, we ensure that each robot can start and end their tasks as early as possible while avoiding collisions with nearby robots. By integrating the space-time RRT* planner (ST-RRT*) into CoMuDi, we ensure that individual tasks minimize arrival time and thereby help us minimize overall makespan. We compare the performance of CoMuDi using both ST-RRT* and RRT* planners with varying time bounds, demonstrating that the combination of CoMuDi and ST-RRT* leads to a higher success rate while minimizing makespan. Finally, we evaluate CoMuDi on six assemblies with up to 49 pieces and up to 9 robots. In those scenarios, we show that CoMuDi returns robot paths that exhibit low idle times, thereby demonstrating that CoMuDi can reliably solve large-scale assemblies.

Problem

• multi-robot coordination
• disassembly planning
• makespan optimization
• task and motion planning
• confined workspace

Innovation

• CoMuDi
• makespan optimization
• multi-robot coordination
• ST-RRT*
• disassembly planning