A CAD-Free Vision-Guided Framework for Robotic Deburring of Flexible Shoe Soles

Abstract

Robotic sole deburring is a key, yet underexplored, challenge in footwear automation, where the deformable nature of rubber, variability of burrs, and diversity of sole geometries make automation difficult. Existing deburring approaches typically rely on CAD models or large training datasets, and often lack the ability to adapt online during execution. This paper presents a CAD-free, vision-guided framework for robotic deburring of shoe soles that integrates: (i) defect detection using the Segment Anything Model 2 without sole-specific training; (ii) motion planning for burr removal; and (iii) motion execution combining Forward Dynamics Compliance Control with online vision-based path tracking. The framework was validated on a UR5e robot equipped with a custom vacuum gripper. Results demonstrate a 95% success rate across soles of varying sizes, colors, and shapes. By eliminating CAD dependence, ensuring robust online correction, and maintaining compatibility with existing industrial deburring machines, this work provides a scalable step toward robotic finishing solutions in footwear manufacturing.