A Tactile Rubbing Gripper for Reliable Fabric Separation
Zhengrong Ling, Zhenghao Huang, Yajing Shen
Abstract
Automated fabric manipulation offers great potential for reducing labor requirements in textile manufacturing and domestic services. Yet, even the basic task of separating a single fabric layer poses substantial challenges for robots. Adhesive-based end-effectors suffer from limited material compatibility and environmental adaptability, while gripper-based designs, which primarily target crease grasping and rely on passive separation, frequently demonstrate unreliability. Current vision and tactile systems fail to detect the fabric separation surface. Given these mechanical and sensing constraints, existing separation solutions lack the ability to adjust the number of layers post-grasping, relying solely on single-attempt success. In this work, we propose a novel tactile-enhanced gripper capable of human-like rubbing motion for reliable cloth separation, which integrates a magnetic sensing system to monitor the separation process. Based on these, we further develop a pipeline to realize rubbing-based separation. Extensive experiments show our gripper achieves a 96.67% separation success rate across 15 fabrics with varying weaving patterns, and the tactile system reaches 87.00% accuracy in sliding surface detection. Our work provides a novel mechanism for fabric layer separation, facilitating subsequent cloth manipulation.