Using adjustable autonomy and human–machine cooperation to make a human–machine system resilient – Application to a ground robotic system

Abstract

This study concerns autonomous ground vehicles performing missions of observation or surveillance. These missions are accomplished under the supervision of human operators, who can also remotely control the unmanned vehicle. This kind of human–machine system is likely to face perturbations in a dynamic natural environment. However, human operators are not able to manage perturbations due to overload. The objective of this study is to provide such systems with ways to anticipate, react and recover from perturbations. In other words, these works aim at improving system resilience so that it can better manage perturbations. This paper presents a model of human–robot cooperative control that helps to improve the resilience of the human–machine system by making the level of autonomy adjustable. A formalism of agent autonomy is proposed according to the semantic aspects of autonomy and the agent’s activity levels. This formalism is then used to describe the activity levels of the global human–machine system. Hierarchical decision-making methods and planning algorithms are also proposed to implement these levels of activity. Finally, an experimental illustration on a micro-world is presented in order to evaluate the feasibility and application of the proposed model.