Hierarchical Planning and Scheduling for Reconfigurable Multi-Robot Disassembly Systems under Structural Constraints

2025-09-17

AI Summary

Automated non-destructive disassembly of reconfigurable multi-robot systems under structural constraints remains challenging, as existing approaches often converge to local optima and fail to jointly optimize task planning, action allocation, and motion coordination. Method: This paper proposes a hierarchical planning and scheduling framework: at the high level, a constraint-aware chromosome initialization strategy is integrated with a multi-objective genetic algorithm to jointly optimize disassembly sequences and task assignments, augmented by motion feasibility evaluation; at the low level, constraint programming enables precise time–resource scheduling. Contribution/Results: The framework effectively mitigates convergence difficulties arising from large-scale search spaces, ensuring structural integrity and operational safety while significantly improving solution quality and computational efficiency. Simulation results demonstrate that the framework generates feasible disassembly plans—satisfying multiple constraints (geometric, mechanical, temporal) and optimizing multiple objectives (makespan, energy consumption, stability)—within reasonable computation time.

Technology Category

• Intelligent Robots: Multi-Robot Systems
• Planning, Routing, and Scheduling: Replanning and Plan Repair
• Multiagent Systems: Multiagent Planning

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Graph Algorithms and Modeling for the Web: Representation, reconstruction, and subgraph or motif discovery in Web-related graphs
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

This study presents a system integration approach for planning schedules, sequences, tasks, and motions for reconfigurable robots to automatically disassemble constrained structures in a non-destructive manner. Such systems must adapt their configuration and coordination to the target structure, but the large and complex search space makes them prone to local optima. To address this, we integrate multiple robot arms equipped with different types of tools, together with a rotary stage, into a reconfigurable setup. This flexible system is based on a hierarchical optimization method that generates plans meeting multiple preferred conditions under mandatory requirements within a realistic timeframe. The approach employs two many-objective genetic algorithms for sequence and task planning with motion evaluations, followed by constraint programming for scheduling. Because sequence planning has a much larger search space, we introduce a chromosome initialization method tailored to constrained structures to mitigate the risk of local optima. Simulation results demonstrate that the proposed method effectively solves complex problems in reconfigurable robotic disassembly.

Problem

• Planning disassembly sequences for reconfigurable robots under structural constraints
• Optimizing multi-robot coordination to avoid local optima solutions
• Integrating motion-aware task planning with scheduling for robotic disassembly

Innovation

• Hierarchical optimization with genetic algorithms
• Reconfigurable multi-robot system integration
• Chromosome initialization for constrained structures