In the present paper, we propose a novel system-driven adaptive shared control framework in which the autonomous system allocates the authority among the human operator and itself. Authority allocation is based on a metric derived from a Bayesian filter, which is being adapted online according to real measurements. In this way, time-varying measurement noise characteristics are incorporated. We present the stability proof for the proposed shared control architecture with adaptive authority allocation, which includes time delay in the communication channel between the operator and the robot. Furthermore, the proposed method is validated through experiments and a user-study evaluation. The obtained results indicate significant improvements in task execution compared with pure teleoperation.

Adaptive Authority Allocation in Shared Control of Robots Using Bayesian Filters / Balachandran, R.; Mishra, H.; Cappelli, M.; Weber, B.; Secchi, C.; Ott, C.; Albu-Schaeffer, A.. - (2020), pp. 11298-11304. (Intervento presentato al convegno 2020 IEEE International Conference on Robotics and Automation, ICRA 2020 tenutosi a fra nel 2020) [10.1109/ICRA40945.2020.9196941].

Adaptive Authority Allocation in Shared Control of Robots Using Bayesian Filters

Cappelli M.;Secchi C.;
2020

Abstract

In the present paper, we propose a novel system-driven adaptive shared control framework in which the autonomous system allocates the authority among the human operator and itself. Authority allocation is based on a metric derived from a Bayesian filter, which is being adapted online according to real measurements. In this way, time-varying measurement noise characteristics are incorporated. We present the stability proof for the proposed shared control architecture with adaptive authority allocation, which includes time delay in the communication channel between the operator and the robot. Furthermore, the proposed method is validated through experiments and a user-study evaluation. The obtained results indicate significant improvements in task execution compared with pure teleoperation.
2020
2020 IEEE International Conference on Robotics and Automation, ICRA 2020
fra
2020
11298
11304
Balachandran, R.; Mishra, H.; Cappelli, M.; Weber, B.; Secchi, C.; Ott, C.; Albu-Schaeffer, A.
Adaptive Authority Allocation in Shared Control of Robots Using Bayesian Filters / Balachandran, R.; Mishra, H.; Cappelli, M.; Weber, B.; Secchi, C.; Ott, C.; Albu-Schaeffer, A.. - (2020), pp. 11298-11304. (Intervento presentato al convegno 2020 IEEE International Conference on Robotics and Automation, ICRA 2020 tenutosi a fra nel 2020) [10.1109/ICRA40945.2020.9196941].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1249387
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