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This paper addresses the challenge of maintaining stable support during the robotic disassembly of irregularly shaped products by introducing a modular vacuum-based fixturing system that plans a unified support configuration across the entire disassembly process. By utilizing a denoising diffusion probabilistic model to generate physics-informed initial configurations, the system refines these layouts through Bayesian optimization, ensuring that the fixture remains effective as components are removed. Experimental results show that the proposed layouts achieved mean empirical stability margins of 66.9% for screwdrivers and 81.6% for shavers, confirming their effectiveness in maintaining support throughout the disassembly sequence.
A modular fixturing system can maintain stability across robotic disassembly stages, achieving impressive stability margins of over 80% for complex products.
Stable support remains challenging in robotic disassembly of irregularly shaped products. As components are progressively removed, the available support surfaces, mass distribution, and task loads change throughout the process. A fixture layout designed for one workpiece state may therefore become infeasible at later stages, motivating unified support planning over the complete disassembly sequence. This paper presents a modular vacuum-based fixturing system that plans one shared support configuration for the complete disassembly sequence of a screwdriver or shaver, allowing each sequence to proceed without fixture reconfiguration. To search the mixed continuous--discrete layout space under repeated cross-stage evaluation, a denoising diffusion probabilistic model generates physics-informed initial configurations that are refined through Bayesian optimization. Robotic screw and component-removal experiments verified the disassembly feasibility of the planned layouts, while 11 directional-load tests quantified their stability. Comparisons between the measured operational loads and directional responses yielded mean empirical stability margins of 66.9% for the screwdriver and 81.6% for the shaver. These results demonstrate that a product-specific shared layout can provide stable support throughout the tested robotic disassembly sequence.
