Improving Task Performance through High Level Shared Control of Multiple Robots with a Context Aware Human-Robot Interface

Abstract

Abstract-In multi-robot control, robots need the ability to perform well in the absence of valid human input. This paper describes a shared control scheme for multiple robots where control can be traded between human and autonomous agents on the fly, reducing the negative effect of robots requiring attention while the user's attention is devoted elsewhere. The control approach is a hybrid of traded control where the control is traded between the human and autonomous agents and coordinated control where high level human user commands are mapped to low level implementation under partial control of the autonomous system. An allocation authority decides whether the user or autonomous agent is controlling the robot at a given time based on a command context. This allocation authority control scheme is compared to a coordinated control scheme in a multirobot soccer domain. The results demonstrate that an allocation authority approach produces improved task performance and may have generalizable applicability. Specifically in the context of robotic soccer, the proposed control scheme was shown to have 18.5% more possession and 8.2% more territory than traded control while also reducing mental demands on users.

A Cooperative Shared Control Scheme Based on Intention Recognition for Flexible Assembly Manufacturing

“…Additionally, Amirshirzad et al ( 2019 ) proposed a human adaptation approach to instantiate the shared control method in a ball balancing HRC task. O'Keeffe et al ( 2016 ) developed a high level of shared control to allocate authority to the robot and the human and improve the task performance in a multirobot system. Further, Fang et al ( 2018 ) and Islam et al ( 2018 ) presented optimization- and impedance-based shared control methods to facilitate the interaction between robots in a multirobot system.…”