Coordinating with Humans by Adjustable-autonomy for Multirobot Pursuit (CHAMP)

The need to fight and control the urban terrain is not a new concept for the military; however, there are new obstacles, illustrated in the battles fought and won in Fallujah and Haditha, that make the job of the warfighter much harder. Due to the pioneering work of researchers in the field of robotics and artificial intelligence, there exist promising and significant opportunities for the incorporation of semi-autonomous robotic entities within the small-unit tactical team that may positively impact the day to day effectiveness of the team. To achieve this vision, we propose to develop a system for Coordinating with Humans by Adjustable-autonomy for Multirobot Pursuit (CHAMP). The robots and humans will be controlled by distributed optimization strategies, derived from results in distributed pursuit, distributed constraint optimization, and dynamic game theory. The degree of operator control will be dynamic, and will be informed by recent results from the field of adjustable autonomy. Finally, the control strategies will be determined by a Cognitive Work Analysis. The CHAMP approach will allow the coordination of the robotic team to become more dynamic and adjust to the goals, demands, and constraints of the current situation as it unfolds.