Physical Human-Robot Interaction for Grasping in Augmented Reality via Rigid-Soft Robot Synergy
🤖 AI Summary
This work addresses the challenges of modeling complexity, perceptual uncertainty, and cross-domain motion coordination faced by hybrid rigid-soft robots operating in unstructured environments. The authors propose an augmented reality (AR)-based physical human–robot interaction framework that enables intuitive teleoperation of rigid-soft hybrid robots through AR headsets and facilitates task rehearsal—particularly for grasping—in a virtual environment integrated with a general-purpose physics engine. A novel parameter identification pipeline is introduced to bridge the real system and its simulation, leveraging the geometric properties of soft components to ensure behavioral consistency between virtual and physical domains. Experimental results demonstrate that the proposed approach significantly enhances fidelity between simulated and real robot behaviors, allowing users to safely and efficiently rehearse and execute complex manipulation tasks.
Application Category
📝 Abstract
Hybrid rigid-soft robots combine the precision of rigid manipulators with the compliance and adaptability of soft arms, offering a promising approach for versatile grasping in unstructured environments. However, coordinating hybrid robots remains challenging, due to difficulties in modeling, perception, and cross-domain kinematics. In this work, we present a novel augmented reality (AR)-based physical human-robot interaction framework that enables direct teleoperation of a hybrid rigid-soft robot for simple reaching and grasping tasks. Using an AR headset, users can interact with a simulated model of the robotic system integrated into a general-purpose physics engine, which is superimposed on the real system, allowing simulated execution prior to real-world deployment. To ensure consistent behavior between the virtual and physical robots, we introduce a real-to-simulation parameter identification pipeline that leverages the inherent geometric properties of the soft robot, enabling accurate modeling of its static and dynamic behavior as well as the control system's response.
Problem
Research questions and friction points this paper is trying to address.
hybrid rigid-soft robot
physical human-robot interaction
augmented reality
grasping
coordination
Innovation
Methods, ideas, or system contributions that make the work stand out.
rigid-soft robot
augmented reality
physical human-robot interaction
parameter identification
teleoperation
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