Resilience of a human-robot system using adjustable autonomy and human-robot collaborative control

Unmanned ground vehicles tend to be more and more autonomous. Nowadays, both complete teleoperation and full autonomy are not efficient enough to deal with all possible situations. To be efficient, the human-robot system must be able to anticipate, react, recover and even learn from errors of different kinds, i.e., to be resilient. Adjustable autonomy is a way to react to unplanned events and to optimise the task allocation between the human operator and the robot. It thus can be seen as a component of the resilience of a system which can be defined as the ability to maintain or recover a stable state when subject to disturbance. In this paper, adjustable autonomy and human-robot cooperation are considered as means to control the resilience. This paper then proposes an approach to design a resilient human-robot system through some defined criteria which aim at assessing the transitions of the modes of autonomy. Perspectives of this approach intend to provide metrics for the adjustment of autonomy in the most resilient way. First results from experiments achieved on a micro-world aim at a preliminary assessment of the different meanings of resilience of the system using the proposed metrics.