As the amount of used home appliances is expected to increase despite the decreasing labor force in Japan, there is a need to automate disassembling processes at recycling plants. The automation of disassembling air conditioner outdoor units, however, remains a challenge due to unit size variations and exposure to dirt and rust. To address these challenges, this study proposes an automated system that integrates a task-specific two-stage detection method and a lattice-based local calibration strategy. This approach achieved a screw detection recall of 99.8% despite severe degradation and ensured a manipulation accuracy of +/-0.75 mm without pre-programmed coordinates. In real-world validation with 120 units, the system attained a disassembly success rate of 78.3% and an average cycle time of 193 seconds, confirming its feasibility for industrial application.
@article{arxiv.2603.29363,
title = {Industrial-Grade Robust Robot Vision for Screw Detection and Removal under Uneven Conditions},
author = {Tomoki Ishikura and Genichiro Matsuda and Takuya Kiyokawa and Kensuke Harada},
journal= {arXiv preprint arXiv:2603.29363},
year = {2026}
}