Shared Autonomy Assisted by Impedance-Driven Anisotropic Guidance Field

2026-05-04

AI Summary

This work addresses the inefficiency in current shared autonomy systems stemming from insufficient bidirectional intent understanding between humans and robots. To overcome this limitation, the authors propose an impedance control–based anisotropic guidance field method that dynamically modulates the robot’s responsiveness to human input, thereby establishing an intuitive, continuous, and embodied communication channel during physical interaction. This approach enables seamless bidirectional intent exchange and mutual guidance without requiring any additional interface. Notably, it is the first to integrate anisotropic guidance fields into a shared autonomy framework, demonstrating significant improvements in task performance, human–robot alignment, and subjective user experience across three distinct tasks and two teleoperation interfaces.

Abstract

Shared autonomy (SA) enables robots to infer human intent and assist in its achievement. While most research focuses on improving intent inference, it overlooks whether humans can understand the robot's intent in return. Without such mutual understanding, collaboration becomes less effective, degrading user experience and task performance. To address this gap, previous studies have explicitly conveyed the robot intent through additional interfaces, which remain unintuitive and limited in expressiveness. Inspired by impedance control, we propose Impedance-Driven Anisotropic Guidance Field Enhanced Shared Autonomy (IAGF-SA), a novel paradigm that extends SA with an embodied, physically-grounded communication channel. This channel adaptively modulates the robot's dynamic response to human input, enabling intuitive, continuous, physically-grounded robot intent communication while naturally guiding human actions. User studies across three scenarios and two teleoperation interfaces indicate that IAGF-SA improves task performance, human-robot agreement, and subjective experience, thus demonstrating its effectiveness in enhancing human-robot communication and collaboration.

Problem

• Shared Autonomy
• Human-Robot Collaboration
• Intent Communication
• Mutual Understanding
• Impedance Control

Innovation

• Shared Autonomy
• Impedance Control
• Anisotropic Guidance Field
• Human-Robot Collaboration
• Physical Communication