When interacting with unmodelled dynamic systems, a robot controller should be capable of adapting online its behavior, in order to be robust to the changing environmental conditions. In the paradigm of passivity-based control, virtual energy tanks allow to perform such adaptations in a robustly stable way, by bounding the amount of energy allocated to the controller. Nevertheless, when the workspace is shared with human collaborators, additional limits have to be imposed to the power the system can exert, in order to guarantee the overall safety. These bounds are difficult to estimate a priori, might vary over time and can significantly affect task execution. In this letter, we tackle this problem by simultaneously adapting online the admittance and the power limits in the controller, ensuring both safety and task performance. Experimental results with a collaborative manipulator validate the presented framework.
Unified Power and Admittance Adaptation for Safe and Effective Physical Interaction With Unmodelled Dynamic Environments / Benzi, F.; Secchi, C.. - In: IEEE ROBOTICS AND AUTOMATION LETTERS. - ISSN 2377-3766. - 8:12(2023), pp. 8279-8286. [10.1109/LRA.2023.3327679]
Unified Power and Admittance Adaptation for Safe and Effective Physical Interaction With Unmodelled Dynamic Environments
Benzi F.;Secchi C.
2023
Abstract
When interacting with unmodelled dynamic systems, a robot controller should be capable of adapting online its behavior, in order to be robust to the changing environmental conditions. In the paradigm of passivity-based control, virtual energy tanks allow to perform such adaptations in a robustly stable way, by bounding the amount of energy allocated to the controller. Nevertheless, when the workspace is shared with human collaborators, additional limits have to be imposed to the power the system can exert, in order to guarantee the overall safety. These bounds are difficult to estimate a priori, might vary over time and can significantly affect task execution. In this letter, we tackle this problem by simultaneously adapting online the admittance and the power limits in the controller, ensuring both safety and task performance. Experimental results with a collaborative manipulator validate the presented framework.
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