Abstract
This paper presents a novel search-path optimization method for moving target search by an aerial vehicle, applicable to realistically sized search areas. For such missions, long endurance vehicles are needed, which are usually fixed-winged. The proposed method accounts for flight kinematics of fixed-wing and rotary-wing aerial vehicles. It additionally accounts for movements of the target, considerably increasing complexity of search-path optimization, compared to a static target. The objective is to maximize the probability to detect a conditionally deterministic moving target within a given time period. We propose a first K-step-lookahead planning method that takes flight kinematic constraints into account and in which the target and platform state space are heterogeneous. It consists of a binary integer linear program that yields a physically feasible search-path, while maximizing the probability of detection. It is based on the Max-K-Coverage problem, as it selects K waypoints while maximizing the probability that a target is within the field of view of a platform at one of these waypoints. This K-step-lookahead planning method is embedded in an iterative framework, where the probability of overlooking a target is fed back to the controller after observations are made. Simulations show the applicability and effectiveness of this method.
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Acknowledgments
This work is supported by Airbus Defence and Space, Germany. We are grateful to Airbus Defense and Space employees Kai Kostorz and Dr. Axel Luthardt for their valuable feedback. Moreover, our gratitude goes to the anonymous reviewers for their insightful comments.
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Communicated by Kyriakos G. Vamvoudakis.
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Raap, M., Meyer-Nieberg, S., Pickl, S. et al. Aerial Vehicle Search-Path Optimization: A Novel Method for Emergency Operations. J Optim Theory Appl 172, 965–983 (2017). https://doi.org/10.1007/s10957-016-1014-y
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DOI: https://doi.org/10.1007/s10957-016-1014-y