TEGA: A Tactile-Enhanced Grasping Assistant for Assistive Robotics via Sensor Fusion and Closed-Loop Haptic Feedback

TL;DR

TEGA is a novel assistive teleoperation system that combines sensor fusion and real-time haptic feedback to improve grasp force control for users with disabilities, enhancing stability and success in manipulation tasks.

Contribution

The paper introduces TEGA, a closed-loop framework integrating EMG-based force inference with visuotactile sensing and haptic feedback for improved grasp force modulation.

Findings

Significantly improved grasp stability in user studies

Enhanced task success rates with TEGA system

Effective real-time tactile feedback for force adjustment

Abstract

Recent advances in teleoperation have enabled sophisticated manipulation of dexterous robotic hands, with most systems concentrating on guiding finger positions to achieve desired grasp configurations. However, while accurate finger positioning is essential, it often overlooks the equally critical task of grasp force modulation, vital for handling objects of diverse hardness, texture, and shape. This limitation poses a significant challenge for users, especially individuals with upper limb disabilities who lack natural tactile feedback and rely on indirect cues to infer appropriate force levels. To address this gap, We present the tactile enhanced grasping assistant (TEGA), a closed loop assistive teleoperation framework that fuses EMG based intent2force inference with visuotactile sensing mapped into real time vibrotactile feedback via a wearable haptic vest, enabling intuitive, proportional force adjustment during manipulation. A wearable haptic vest delivers real time tactile feedback, allowing users to dynamically refine grasp force during manipulation. User studies confirm that the system substantially improves grasp stability and task success, underscoring its potential for assistive robotic applications.