Industrial-Grade Robust Robot Vision for Screw Detection and Removal under Uneven Conditions

2026-03-31

AI Summary

This study addresses the challenges of automating air conditioner outdoor unit disassembly, where high model variability and degraded screw conditions—such as corrosion and contamination—render conventional vision-based localization methods ineffective. To overcome these issues, the authors propose a task-specific two-stage screw detection algorithm coupled with a grid-based local camera calibration strategy, enabling an industrial robotic vision system that operates without pre-defined coordinate references. The integrated system combines highly robust visual perception with precise robotic control, achieving sub-millimeter operational accuracy under complex degradation scenarios. Evaluated on 120 real-world units, the system attains a screw detection recall rate of 99.8%, a successful disassembly rate of 78.3%, and an average cycle time of 193 seconds.

Abstract

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.

Problem

• screw detection
• robot vision
• disassembly automation
• industrial robotics
• recycling

Innovation

• two-stage detection
• lattice-based calibration
• screw detection
• robot vision
• industrial automation