Date/Time
Date(s) - April 05, 2019
11:45 am - 12:35 pm
Location
234 Weil Hall
Categories
Young-Jun Son, Ph.D.
Professor & Head
Systems & Industrial Engineering Department, University of Arizona
Abstract: A DDDAMS-based Surveillance and Crowd Control via UAVs and UGVs
In this talk, we first introduce a dynamic data driven adaptive multi-scale simulation (DDDAMS) based planning and control framework that we have developed for effective and efficient surveillance and crowd control via unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs). The framework is composed of integrated planner, integrated controller, and decision module for DDDAMS. The integrated planner, which is designed in an agent-based simulation (ABS) and Unity-based game engine, devises best control strategies for each function of 1) crowd detection, 2) crowd tracking, and 3) UAV/UGV motion planning. The integrated controller then controls real UAVs/UGVs for surveillance tasks via 1) sensory data collection and processing, 2) control command generation based on strategies provided by the decision planner, and 3) control command transmission via radio to the real system. The decision module for DDDAMS enhances computational efficiency of the framework via dynamic switching of fidelity of simulation and information gathering. Finally, we will share the results of our field demo, which successfully integrated a fast running simulator, a real-time simulator, and the real system (viz. UAVs, UGVs, and crowd).