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Related Experiment Video

Updated: Jan 17, 2026

Adaptation of a Haptic Robot in a 3T fMRI

Adaptation of a Haptic Robot in a 3T fMRI

Published on: October 4, 2011

Towards a Multifidelity Digital Human Model for Use in Simulation Environments for Tactile Human/Robot Interactions.

Rajarshi Roy¹, Qianwen Zhao², Aldrin Padua²

¹Corvid Technologies, Mooresville, NC 28117, United States.

Military Medicine

|September 23, 2025

Summary

This summary is machine-generated.

A new multifidelity digital human model (M-DHM) integrates low- and high-fidelity models for safer robotic casualty extraction. This advanced simulation tool enhances human-robot interaction planning for rescue missions.

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Area of Science:

Robotics and Autonomous Systems (RAS)
Human-Robot Interaction (HRI)
Computational Biomechanics

Background:

Increasing interest in RAS for battlefield casualty extraction and medical interventions.
Current digital human models (DHMs) lack biofidelity and scalability for robotic simulations.
Need for accurate human modeling in robotic manipulation to prevent further injury during Human-Robot Interaction (HRI).

Purpose of the Study:

To develop a multifidelity digital human model (M-DHM) suitable for robotic simulation environments.
To integrate low-fidelity multibody dynamics (MD) DHMs with high-fidelity finite-element (FE) DHMs.
To provide path planners with both point and distributed loading data during HRI events.

Main Methods:

Developed a software architecture integrating two low-fidelity MD-DHMs and one high-fidelity FE-DHM.
Enabled exchange of human joint kinematics and applied forces between MD-DHM(s) and FE-DHM.
Developed methods to retrieve multifidelity anatomical loading (M-AL) and estimate it using reduced-order models.

Main Results:

Successfully demonstrated the M-DHM for grasping and palpation of lower arms.
Validated the model for repositioning and dragging of a leg in simulation.
Showcased the model's capability to provide comprehensive loading data for HRI planning.

Conclusions:

The M-DHM advances next-generation planning algorithms for robotic applications.
Potential for military applications, such as search-and-rescue missions.
Future civilian applications include RAS for patient manipulation and healthcare.