Improving tracking through human-robot sensory augmentation

Li, Yanan, Eden, Jonathan, Carboni, Gerolamo and Burdet, Etienne (2020) Improving tracking through human-robot sensory augmentation. IEEE Robotics and Automation Letters. ISSN 2377-3766

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This paper introduces a sensory augmentation technique enabling a contact robot to understand its human user’s control in real-time and integrate their reference trajectory information into its own sensory feedback to improve its tracking performance. The human’s control is formulated as a feedback controller with unknown control gains and desired trajectory. An unscented Kalman filter is used to estimate first the control gains and then the desired trajectory. The estimated human’s desired trajectory is used as augmented sensory information about the system and combined with the robot’s measurement to estimate a reference trajectory. Simulations and an implementation on a robotic interface demonstrate that the reactive control can robustly identify the human user’s control, and that the sensory augmentation improves the robot’s tracking performance.

Item Type: Article
Schools and Departments: School of Engineering and Informatics > Engineering and Design
SWORD Depositor: Mx Elements Account
Depositing User: Mx Elements Account
Date Deposited: 26 May 2020 10:59
Last Modified: 23 Feb 2022 09:49

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Project NameSussex Project NumberFunderFunder Ref
The Game Theory of Human-Robot Interaction - HRIgameG2929EPSRC-ENGINEERING & PHYSICAL SCIENCES RESEARCH COUNCILUnset