Tactile sensing soft fingertip with dual air bag structure for an anthropomorphic robotic hand

Abstract

Tactile sensing plays a crucial role to empower robotic hands with improved grasping and manipulating abilities. In this paper, we propose an anthropomorphic robotic hand design with dual air bag sensors integrated soft fingertips to achieve tactile sensing. The air bag sensor is low-cost, easy-to-build and deformable, and can be embedded in the fingertip, endows the hand with the ability to perceive and makes it have the mechanical complicance similar to the human fingertip. The air bag sensor exhibits high performance metrics, including a sensitivity of ~1.65 kPa/N, a minimum detection force of < 0.01 N, a response time of < 10 ms, and good stability and repeatability. The experimental results show that the proposed robotic hand performs well in surface texture detection, hard inclusion depth detection and object softness detection, as well as grasping tasks. By applying a machine learning algorithm to the experimental data, an accuracy of 0.767 and 0.898 was achieved in predicting hard inclusion depth and object hardness, respectively. This study provides a simple and effective tactile sensing solution for the design of anthropomorphic robotic hand, and may have possible applications such as end-effectors for humanoid robots or robotic palpation.