Coordinated maneuver in ground robotics for multiagent systems

Abstract

Robots moving in formations can serve as the core functionality of coordinated maneuvers, which have realworld applications for logistics-based tasks, mobile asset protection, environmental monitoring, or wide-area surveillance. In order for autonomous multi-robot systems to be useful in such applications, they must be able to seamlessly execute actions, strategies, and behaviors in a coordinated manner. An example of coordinated behavior in multi-robot systems is the movement of robots across terrain in various geometric formations. The general goal of this work is to leverage formations inspired by military mobility and maneuver to guide the behaviors of autonomous multi-robot systems. Generally, our approach aims to develop coordinated multi-robot behaviors by utilizing domain knowledge to guide multi-agent systems. In this work, we measure a globalplanning based approach for control of a multi-robot system that is tasked with executing specific geometric formations in a Robot Operating System (ROS) based photo-realistic simulation environment (ARL Unity ROS Simulator (AURS)). This work highlights a quantitative assessment of global-planning based approaches for executing simple multi-robot coordinated behavior. Finally, the results of these experiments establish a baseline by providing metrics to evaluate a set of global navigation planners using a planning only approach to multi-agent coordinated maneuver.