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Optimal UAV Sensor Management and Path Planning for Tracking Multiple Mobile Targets

[+] Author Affiliations
Negar Farmani, Liang Sun, Daniel Pack

The University of Texas at San Antonio, San Antonio, TX

Paper No. DSCC2014-6232, pp. V002T25A003; 8 pages
  • ASME 2014 Dynamic Systems and Control Conference
  • Volume 2: Dynamic Modeling and Diagnostics in Biomedical Systems; Dynamics and Control of Wind Energy Systems; Vehicle Energy Management Optimization; Energy Storage, Optimization; Transportation and Grid Applications; Estimation and Identification Methods, Tracking, Detection, Alternative Propulsion Systems; Ground and Space Vehicle Dynamics; Intelligent Transportation Systems and Control; Energy Harvesting; Modeling and Control for Thermo-Fluid Applications, IC Engines, Manufacturing
  • San Antonio, Texas, USA, October 22–24, 2014
  • Conference Sponsors: Dynamic Systems and Control Division
  • ISBN: 978-0-7918-4619-3
  • Copyright © 2014 by ASME


In this paper, we present an optimal sensor manager and a path planner for an Unmanned Aerial Vehicle (UAV) to geo-localize multiple mobile ground targets. A gimbaled camera with a limited field of view (FOV) and a limited range is used to capture targets, whose states are estimated using a set of Extended Kalman Filters (EKFs). The sensor management is performed using a dynamic weighted graph and a Model Predictive Control (MPC) technique, determining the optimal gimbal pose that minimizes the overall uncertainty of target states. A UAV path planner that maximizes a novel cost function is employed to support the sensor management. Simulation results show the effectiveness of the proposed sensor manager and the path planner.

Copyright © 2014 by ASME



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