Minimally-Back-Drivable Robots for Rehabilitation: Path-Adherent Permissiveness Control via Trajectory Adaptation
Erfan Shahriari, Johannes Lachner, Sami Haddadin, Neville Hogan
Abstract
In pursuit of effective robot-assisted rehabilitation, it is imperative that the robot facilitates rather than hinders the patient's self-movements in appropriate directions. This essential attribute, termed <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">permissiveness</i>, is often lacking in conventional industrial robots. In this letter, an innovative approach is introduced, enabling the robot to provide a controlled degree of permissiveness in specified directions. Central to the method is a novel mapping function that dynamically adjusts the desired trajectory along the therapeutic path in response to the patient's monitored physical effects. The proposed approach is agnostic to the type of controlled robot employed, rendering even minimally-back-drivable robots viable for rehabilitation purposes. The letter outlines the approach's diverse facets and potential applications, including an iterative phase-based support adaptation policy, and a series of experiments showcasing the practical feasibility.
BibTeX
@inproceedings{ral2025_minimallybackdri,
title = {Minimally-Back-Drivable Robots for Rehabilitation: Path-Adherent Permissiveness Control via Trajectory Adaptation},
author = {Erfan Shahriari and Johannes Lachner and Sami Haddadin and Neville Hogan},
booktitle = {RA-L 2025},
year = {2025}
}