Razmjoo, A., Brecelj, T., Savevska, K., Ude, A., Petric, T. and Calinon, S. (2023)
Learning Joint Space Reference Manifold for Reliable Physical Assistance
In Proc. IEEE/RSJ Intl Conf. on Intelligent Robots and Systems (IROS).
Abstract
This paper presents a study on the use of the Talos humanoid robot for performing assistive sit-to-stand or stand-to-sit tasks. In such tasks, the human exerts a large amount of force (100-200 N) within a very short time (2-8 s), posing significant challenges in terms of human unpredictability and robot stability control. To address these challenges, we propose a novel approach for finding a spatial reference for the robot, which allows the robot to move according to the force exerted by the human and control its stability during the task. Specifically, we focus on the problem of finding an optimal path for the robot, while assuming a simple controller to guide its movement. To achieve this, we use motion primitives to parameterize the spatial reference and solve an optimization problem that takes into account the robot's stability and the unpredictability of human behavior. We demonstrate the effectiveness of our approach through simulations and experiments with the Talos robot, showing robustness and adaptability.
Bibtex reference
@inproceedings{Razmjoo23IROS,
author="Razmjoo, A. and Brecelj, T. and Savevska, K. and Ude, A. and Petric, T. and Calinon, S.",
title="Learning Joint Space Reference Manifold for Reliable Physical Assistance",
booktitle="Proc.\ {IEEE/RSJ} Intl Conf.\ on Intelligent Robots and Systems ({IROS})",
year="2023",
pages=""
}