Bi-directional Momentum-based Haptic Feedback and Control System for In-Hand Dexterous Telemanipulation

TL;DR

This paper introduces a compact, real-time bi-directional haptic feedback system for in-hand telemanipulation that improves torque rendering and operator perception using a momentum-based mechanism and adaptive feedback strategies.

Contribution

The paper presents a novel palm-sized momentum-actuated haptic device with integrated IMU and adaptive feedback for enhanced dexterous telemanipulation.

Findings

Low command following latency (<0.025 s) achieved.

High torque feedback accuracy (RMSE < 0.010 Nm).

Effective in-hand haptic feedback demonstrated.

Abstract

In-hand dexterous telemanipulation requires not only precise remote motion control of the robot but also effective haptic feedback to the human operator to ensure stable and intuitive interactions between them. Most existing haptic devices for dexterous telemanipulation focus on force feedback and lack effective torque rendering, which is essential for tasks involving object rotation. While some torque feedback solutions in virtual reality applications-such as those based on geared motors or mechanically coupled actuators-have been explored, they often rely on bulky mechanical designs, limiting their use in portable or in-hand applications. In this paper, we propose a Bi-directional Momentum-based Haptic Feedback and Control (Bi-Hap) system that utilizes a palm-sized momentum-actuated mechanism to enable real-time haptic and torque feedback. The Bi-Hap system also integrates an Inertial Measurement Unit (IMU) to extract the human's manipulation command to establish a closed-loop learning-based telemanipulation framework. Furthermore, an error-adaptive feedback strategy is introduced to enhance operator perception and task performance in different error categories. Experimental evaluations demonstrate that Bi-Hap achieved feedback capability with low command following latency (Delay < 0.025 s) and highly accurate torque feedback (RMSE < 0.010 Nm).