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

2024-09-30

arXiv.org

AI Summary

Current dexterous teleoperation haptic devices commonly lack effective torque feedback, resulting in human-robot torque mismatch during object rotation/rolling tasks; conventional torque solutions suffer from mechanical redundancy and poor portability. This paper proposes a lightweight haptic feedback system based on bidirectional momentum wheels, introducing for the first time a unified bidirectional momentum-driven mechanism that integrates torque and vibrotactile rendering. We design an error-adaptive feedback strategy leveraging multimodal perception, a learning-based controller, and field-oriented control (FOC)-driven brushless momentum wheels. Implemented atop a low-latency real-time communication architecture, the system achieves tactile latency <0.025 s and torque feedback RMSE <0.010 Nm. By transcending pure force feedback limitations, our approach significantly improves task completion rate, user confidence, and situational awareness in rotational manipulation.

Technology Category

• Intelligent Robots: Manipulation
• Humans and AI: Interaction Techniques and Devices
• Cognitive Modeling & Cognitive Systems: Adaptive Behavior

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems

Abstract

Haptic feedback is essential for dexterous telemanipulation that enables operators to control robotic hands remotely with high skill and precision, mimicking a human hand's natural movement and sensation. However, current haptic methods for dexterous telemanipulation cannot support torque feedback, resulting in object rotation and rolling mismatches. The operator must make tedious adjustments in these tasks, leading to delays, reduced situational awareness, and suboptimal task performance. This work presents a Bi-directional Momentum-based Haptic Feedback and Control (Bi-Hap) system for real-time dexterous telemanipulation. Bi-Hap integrates multi-modal sensors to extract human interactive information with the object and share it with the robot's learning-based controller. A Field-Oriented Control (FOC) algorithm is developed to enable the integrated brushless active momentum wheel to generate precise torque and vibrative feedback, bridging the gap between human intent and robotic actions. Different feedback strategies are designed for varying error states to align with the operator's intuition. Extensive experiments with human subjects using a virtual Shadow Dexterous Hand demonstrate the effectiveness of Bi-Hap in enhancing task performance and user confidence. Bi-Hap achieved real-time feedback capability with low command following latency (delay<0.025s) and highly accurate torque feedback (RMSE<0.010 Nm).

Problem

• Enables real-time haptic and torque feedback for in-hand telemanipulation
• Addresses lack of portable torque feedback in existing haptic devices
• Improves operator perception with error-adaptive feedback strategy

Innovation

• Palm-sized momentum-actuated haptic feedback mechanism
• IMU-integrated closed-loop learning telemanipulation framework
• Error-adaptive strategy enhancing perception and performance