Fall Detection and Prevention in a Lower Limb Exoskeleton Using MuJoCo Simulation

Forouzan Salehi Fergeni; Tianyu Wang; Steffen Leonhardt; Marian Walter

doi:10.18416/AUTOMED.2026.2506

Proceedings on Automation in Medical Engineering
Vol. 3 No. 1 (2026): Proc AUTOMED
https://doi.org/10.18416/AUTOMED.2026.2506

18th Interdisciplinary AUTOMED Symposium in Collaboration with the TC Medical Robotics, 2506

Fall Detection and Prevention in a Lower Limb Exoskeleton Using MuJoCo Simulation

Forouzan Salehi Fergeni (Institute of Medical Information Technology, RWTH Aachen University, Aachen, Germany), Tianyu Wang (Institute of Medical Information Technology, RWTH University, Aachen, Germany), Steffen Leonhardt (Institute of Medical Information Technology, RWTH University, Aachen, Germany), Marian Walter (Institute of Medical Information Technology, RWTH University, Aachen, Germany)

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

Exoskeletons are a vital assistive technology for enabling gait in elderly and disabled people. Although there have been some advances in exoskeletons designed for fall protection, further improvements and research are necessary. This paper addresses the issue of fall detection and prevention using exoskeletons. The MuJoCo physics simulator was utilized to develop and test our fall prevention control strategy. The simulation employs a humanoid model coupled with a lower-limb exoskeleton. This single platform integrates gait generation, fall detection, and fall prevention control strategy. The simulation results demonstrate that the system can maintain stable walking, detect disturbances, and prevent falls.

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