Coordinated pursuer control using particle filters for autonomous search-and-capture |
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| Authors: | Chern Ferng Chung Tomonari Furukawa |
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| Affiliation: | 1. Clinical Trial Center, Department of Biostatistics, University of Washington, Seattle, WA, United States;2. University of Washington-Harborview Center for Prehospital Emergency Care, Department of Medicine, University of Washington, Seattle, WA, United States;3. Department of Emergency Medicine, University of Ottawa, Ottawa Health Research Institute, Ottawa, ON, Canada;4. Rescu, Li Ka Shing Knowledge Institute, St Michael''s Hospital and Sunnybrook Center for Prehospital Medicine, Division of Emergency Medicine, Department of Family and Community Medicine, University of Toronto, Toronto, ON, Canada;5. Departments of Emergency Medicine and Internal Medicine, University of Texas Southwestern, Dallas, TX, United States;6. King County EMS, Seattle and King County Public Health, and Department of Medicine, University of Washington, Seattle, WA, United States;7. Wilfrid Laurier University, Waterloo, ON, Canada;8. Clark County Emergency Medical Services, Vancouver, WA, United States;9. Department of Emergency Medicine, University of Pittsburgh, Pittsburgh, PA, United States;10. Toronto Health Economics and Technology Assessment Collaborative, Institute of Health Policy, Measurement and Evaluation, University of Toronto, Toronto, ON, Canada;11. Clackamas Fire District #1, Clackamas, OR, United States;12. Medical College of Wisconsin, Milwaukee, WI, United States;1. National Defense Academy of Japan, Japan;2. Japan Ground Self-Defense Force, Japan;3. Fukuoka Institute of Technology, Japan;4. Japan Air Self-Defense Force, Japan;1. Virginia Tech, Child Study Center, Department of Psychology, Blacksburg, VA 24061, United States;2. Stockholm University, Department of Psychology, SE-106 91 Stockholm, Sweden |
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| Abstract: | In a real-world pursuit-evasion (PE) game, the pursuers often have a limited field-of-view of the evaders and thus are required to search for and detect the evaders before capturing them. This paper presents a unified framework and control algorithm using particle filters (PFs) for the coordination of multiple pursuers to search for and capture multiple evaders given the ability of PF to estimate highly non-Gaussian densities prevalent in search problems. The pursuer control problem is formulated as a stochastic control problem where global objectives function of both searching and capturing are common. To take the evaders’ actions into account, an action measure (AM) is defined over the evaders’ PDs is used to represent the probability that the evader may transit each state in the PD. The global objective functions for search and capture are then decomposed into local objective functions for unification through objective priority weights. Coordination between the pursuers takes place through the multi-sensor update where the observation likelihoods of all pursuers are used in the PF update stage. The control actions of each pursuer are then determined individually, based on the updated PDs given the objective weights, action measures as well as evader importance weights in the case of multiple evaders. The proposed algorithm is tested in three scenarios for its effectiveness. In addition, a parametric study on the average capture time against the initial variances of the target state uncertainty is conducted to test for robustness. Results show that the pursuers are able to capture all the evaders in each case with the capture time for the second and last scenario differing by only 2.9% implying firstly that under the proposed algorithm, the capture time is not proportional to the increase in the number of evaders and also suggested robustness and potential scalability of the proposed algorithm. |
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