SuckTac: Camera-based Tactile Sucker for Unstructured Surface Perception and Interaction

TL;DR

SuckTac is an innovative camera-based tactile sucker inspired by cephalopods, designed for high-fidelity perception and robust manipulation on unstructured surfaces, enhancing robotic interaction capabilities.

Contribution

The paper introduces SuckTac, a novel sucker integrating a camera-based tactile sensor within its structure, enabling detailed surface perception and improved robustness for complex environments.

Findings

High-density perception of surface shape, texture, and roughness achieved.

Enhanced robustness and adaptability demonstrated in cloth manipulation and robot inspection.

Superior performance over traditional suckers in unstructured environments.

Abstract

Suckers are significant for robots in picking, transferring, manipulation and locomotion on diverse surfaces. However, most of the existing suckers lack high-fidelity perceptual and tactile sensing, which impedes them from resolving the fine-grained geometric features and interaction status of the target surface. This limits their robust performance with irregular objects and in complex, unstructured environments. Inspired by the adaptive structure and high-performance sensory capabilities of cephalopod suckers, in this paper, we propose a novel, intelligent sucker, named SuckTac, that integrates a camera-based tactile sensor directly within its optimized structure to provide high-density perception and robust suction. Specifically, through joint structure design and optimization and based on a multi-material integrated casting technique, a camera and light source are embedded into the sucker, which enables in-situ, high-density perception of fine details like surface shape, texture and roughness. To further enhance robustness and adaptability, the sucker's mechanical design is also optimized by refining its profile, adding a compliant lip, and incorporating surface microstructure. Extensive experiments, including challenging tasks such as robotic cloth manipulation and soft mobile robot inspection, demonstrate the superior performance and broad applicability of the proposed system.