Coordinated CRLB-based Control for Tracking Multiple First Responders in 3D Environments
- Authors
- Papaioannou, Savvas; Kim, Sungjin; Laoudias, Christos; Kolios, Panayiotis; Kim, Sunwoo; Theocharides, Theocharis; Panayiotou, Christos; Polycarpou, Marios
- Issue Date
- Sep-2020
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Citation
- 2020 International Conference on Unmanned Aircraft Systems, ICUAS 2020, pp.1475 - 1484
- Indexed
- SCOPUS
- Journal Title
- 2020 International Conference on Unmanned Aircraft Systems, ICUAS 2020
- Start Page
- 1475
- End Page
- 1484
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/3686
- DOI
- 10.1109/ICUAS48674.2020.9213937
- Abstract
- In this paper we study the problem of tracking a team of first responders with a fleet of autonomous mobile flying agents, operating in 3D environments. We assume that the first responders exhibit stochastic dynamics and evolve inside challenging environments with obstacles and occlusions. As a result, the mobile agents probabilistically receive noisy line-of-sight (LoS), as well as non-line-of-sight (NLoS) range measurements from the first responders. In this work, we propose a novel estimation (i.e., estimating the position of multiple first responders over time) and control (i.e., controlling the movement of the agents) framework based on the Cram?r-Rao lower bound (CRLB). More specifically, we analytically derive the CRLB of the measurement likelihood function which we use as a control criterion to select the optimal joint control actions over all agents, thus achieving optimized tracking performance. The effectiveness of the proposed multi-agent multi-target estimation and control framework is demonstrated through an extensive simulation analysis.
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