Compliant Robotic Hand with Integrated Tactile Sensing and Finger Overlap Classification

This paper presents the development of an anthropomorphic robotic hand designed for compliant grasping and intelligent control. Based on the open-source LEAP Hand, the servomotor actuation is tailored to enable passive compliance, a crucial feature for safe and adaptable interaction. A ROS-based modular control architecture is implemented to facilitate manipulation tasks, complemented by a distributed sensing system using piezoresistive sensors on the fingertips and palm for contact detection. A key challenge addressed is undesired finger overlaps during the hand opening sequence, which could lead to internal collisions and increased mechanical stress. To overcome this, a data acquisition pipeline is designed to collect information on finger configurations, which is used to train a multi-layer perceptron (MLP) classifier. This model is trained to identify three critical scenarios: "no overlap," "overlap with thumb underneath," and "overlap with thumb on top," achieving accuracy, precision, recall, and F1-score all above 97%. This highlights its potential to enhance system robustness and support future predictive control strategies for safe and coordinated finger motion.