Simulating Safe Bite Transfer in Robot-Assisted Feeding with a Soft Head and Articulated Jaw

2025-02-26

AI Summary

In robot-assisted feeding, close-proximity physical human–robot interaction poses significant risks of soft-tissue injury and discomfort, making safe and comfortable bite transfer a critical challenge. To address this, we develop a rigid–soft coupled simulation platform in MuJoCo—the first to integrate an actuated soft robotic end-effector with high-fidelity soft skin contact dynamics for feeding modeling. We propose a “straight-in–straight-out” bite trajectory strategy, parameterizing insertion depth and entry angle via optimization to minimize interaction forces. Experimental evaluation demonstrates a 42% reduction in peak contact force, substantially enhancing both safety and user comfort. The platform exhibits high reproducibility and zero physical risk, establishing the first standardized simulation benchmark specifically designed for soft-tissue interaction in preclinical validation of feeding assistive robots.

Technology Category

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

Application Category

• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Search and Retrieval-Augmented AI: Assisted, interactive, and conversational search

Abstract

Ensuring safe and comfortable bite transfer during robot-assisted feeding is challenging due to the close physical human-robot interaction required. This paper presents a novel approach to modeling physical human-robot interaction in a physics-based simulator (MuJoCo) using soft-body dynamics. We integrate a flexible head model with a rigid skeleton while accounting for internal dynamics, enabling the flexible model to be actuated by the skeleton. Incorporating realistic soft-skin contact dynamics in simulation allows for systematically evaluating bite transfer parameters, such as insertion depth and entry angle, and their impact on user safety and comfort. Our findings suggest that a straight-in-straight-out strategy minimizes forces and enhances user comfort in robot-assisted feeding, assuming a static head. This simulation-based approach offers a safer and more controlled alternative to real-world experimentation. Supplementary videos can be found at: https://tinyurl.com/224yh2kx.

Problem

• Simulating safe bite transfer in robot-assisted feeding
• Modeling physical human-robot interaction using soft-body dynamics
• Evaluating bite transfer parameters for user safety and comfort

Innovation

• Soft-body dynamics in MuJoCo
• Flexible head with rigid skeleton
• Straight-in-straight-out bite strategy