Bayesian-Optimized Impedance Control of an Aerial Robot for Safe Physical Interaction with the Environment

Asem Khattab, Ramy Rashad, Johan B.C. Engelen, Stefano Stramigioli

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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Abstract

Impedance control is a widely used interaction-control technique for aerial and ground robots. To achieve consistent performance during impedance control tasks, an a-priori knowledge of the environment parameters is needed to adjust the controller's impedance parameters accordingly. Concentrating on tasks requiring constant impedance parameters throughout operation, a model-free learning framework is proposed to autonomously find the suitable parameters values. The framework relies on Bayesian optimization and episodic reward calculation requiring the drone to repeatedly perform a predetermined task in the environment actively searching in the impedance parameters space. The sample-efficiency and safety of learning were improved by adding two novel modifications to standard Bayesian optimization. The proposed technique was validated in a high fidelity simulation environment. The results show that the proposed framework is able to automatically find suitable impedance parameters values in different situations given the same initial knowledge and that the learned parameters values can be generalized to similar interaction tasks.
Original languageEnglish
Title of host publication2019 IEEE International Symposium on Safety, Security, and Rescue Robotics, SSRR 2019
PublisherIEEE
Pages172-179
Number of pages8
ISBN (Electronic)9781728107783
DOIs
Publication statusPublished - 2 Sept 2019
Event2019 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR) - University of Würzburg Graduate Schools building, Würzburg, Germany
Duration: 2 Sept 20194 Sept 2019
http://ssrr2019.org

Conference

Conference2019 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR)
Abbreviated titleSSRR 2019
Country/TerritoryGermany
CityWürzburg
Period2/09/194/09/19
Internet address

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