pHRI Real2Sim in HITL-Simulation

Pipeline for modeling pHRI with MuJoCo

Identifying and simulating physical human–robot interaction for safe, personalized gait-assistive robots — from standardized MSD parameter identification to soft-body contact modeling.

Beyond Heuristics: A Standardized Real2Sim Pipeline for Physical Human-Robot Interaction in Human-in-the-Loop Simulation

Chengyuan Yang1, Yifan Wang1, Chun Kwang Tan1, Sherwin Stephen Chan1, Youlong Wang1, Xiaoyue Yan1, Lei Li2, Wei Tech Ang1
1Nanyang Technological University, 2Guangdong Zhongxin Intelligent Rehabilitation Research Institute, Foshan, China 528200
Tuning Pipeline for Conventional pHRI MSD Model
BioRob 2026

Abstract

The rapid aging of the global population necessitates scalable assistive robotics; however, development is hindered by the high safety risks and costs associated with physical testing. Human-in-the-Loop (HITL) simulation offers a safe alternative, yet existing frameworks for coupled systems (e.g., gait-assistive robots) often rely on heuristic, manually tuned interaction models that fail to capture the complex dynamics of soft interactions. To bridge this “reality gap,” this paper proposes a comprehensive Real2Sim pipeline for identifying coupled Physical Human-Robot Interaction (pHRI) dynamics. We formulate a generalized six-degrees-of-freedom (6-DoF) viscoelastic model to capture the full spatial compliance of the pelvis-strap interface. Addressing the ambiguity of harness fit across diverse anthropometrics, we employ a psychophysics-constrained optimization strategy where subjective “Safe & Comfortable” feedback serves as a prior to regularize a Covariance Matrix Adaptation Evolution Strategy (CMA-ES) identification process. Furthermore, through statistical analysis, we derive shareable parameter sets that enable rapid, zero-shot configuration for new users. Validation results demonstrate that our calibrated model significantly outperforms manual tuning, reducing trajectory tracking errors and correctly inducing biomechanically accurate gait adaptations in the Human Digital Twin. This approach significantly improves HITL simulation fidelity, thereby enabling the Human Digital Twin to serve as a valid predictive tool for accelerating the pre-clinical verification of personalized controllers.

Effect of Interaction Stiffness on Human Gait

Adjust the pHRI model parameters — slide to a setting and the matching clip plays on its own, showing how the interaction stiffness shapes the walking pattern.

Soft

Optimized

Stiff

 too compliant interaction impedance too rigid 

Results

Working space validation

Working space validation

Gait analysis validation

Gait analysis

BibTeX

@inproceedings{yang2026beyond,
  author    = {Yang, Chengyuan and Wang, Yifan and Tan, Chun Kwang and Chan, Sherwin Stephen and Wang, Youlong and Yan, Xiaoyue and Li, Lei and Ang, Wei Tech},
  title     = {Beyond Heuristics: A Standardized Real2Sim Pipeline for Physical Human-Robot Interaction in Human-in-the-Loop Simulation},
  booktitle = {IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob)},
  year      = {2026},
}

The DRBA Robot

Both works are developed on the same platform — the DRBA assistive robot, which integrates balance, sit-to-stand, and mobility assistance.

DRBA robot system overview: balance, sit-to-stand, and mobility assistance subsystems.

System overview of the DRBA robot — the shared platform for both works: (a) balance assistance, (b) sit-to-stand assistance, and (c) mobility assistance.