A DDDAMS-based UAV and UGV team formation approach for surveillance and crowd control

Amirreza M. Khaleghi, Dong Xu, Sara Minaeian, Mingyang Li, Yifei Yuan, Jian Liu, Young-Jun Son, Christopher Vo, Jyh-Ming Lien

Abstract: The goal of this paper is to study the team formation of multiple UAVs and UGVs for collaborative surveillance and crowd control under uncertain scenarios (e.g. crowd splitting). A comprehensive and coherent dynamic data driven adaptive multi-scale simulation (DDDAMS) framework is adopted, with the focus on simulation-based planning and control strategies related to the surveillance problem considered in this paper. To enable the team formation of multiple UAVs and UGVs, a two stage approach involving 1) crowd clustering and 2) UAV/UGV team assignment is proposed during the system operations by considering the geometry of the crowd clusters and solving a multi-objective optimization problem. For the experiment, an integrated testbed has been developed based on agent-based hardware-in-the-loop simulation involving seamless communications among simulated and real vehicles. Preliminary results indicate the effectiveness and efficiency of the proposed approach for the team formation of multiple UAVs and UGVs.

External IDs:dblp:conf/wsc/KhaleghiXMLYLSV14