Abstract—Individuals with partial lower-limb impairments can benefit from robotic gait rehabilitation to improve muscle memory and coordination. Lower-limb exoskeletons can provide assistance tailored to a patient’s needs, reducing therapist workload by automating the procedure. However, the level of assistance provided by the robot should be carefully controlled to ensure the user receives assist-asneeded support, while remaining actively engaged in the motion. This paper introduces a human-robot interaction estimation technique that enables a self-balancing exoskeleton to assess patient-initiated joint torques using only actuator torque estimations. An admittance controller is employed to adjust the deviation from the desired trajectory based on the user’s effort. The proposed method is validated through both simulation and experimental results focused on swing foot control of a biped (humanoid) exoskeleton. The findings demonstrate the feasibility of the approach and its potential for application in more complex rehabilitation scenarios.

Keywords—robotic gait rehabilitation, self-balancing lower-limb wearable humanoid exoskeletons, assist-asneeded control

Cite: Milad Mousavi, Siamak Arzanpour, and Edward J. Park, "Assist-as-Needed Gait Rehabilitation via Actuator Torque Estimation for a Self-Balancing Lower-Body Exoskeleton," International Journal of Mechanical Engineering and Robotics Research, Vol. 14, No. 4, pp. 430-435, 2025. doi: 10.18178/ijmerr.14.4.430-435

Copyright © 2025 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).