Adaptive Multi-Robot, Multi-Operator Work Systems

Abstract

Unstructured and hostile environments impose great risk to exposed humans and present ideal domains for robotic forces; however, these dynamic environments pose considerable difficulty in autonomous multi-robot coordination, making a need for supervisory control paramount. This paper examines a three-phase approach that increases the robustness, reliability, and efficiency of human-machine work systems by dynamically altering the soldier-robot control relationships as well as the effective autonomy manifested by each robot function in response to estimated cognitive loading (stress). This approach enables an adaptive command and control structure across a spectrum of force configurations.