Abstract
This paper is interested in the problem of monitoring and cleaning dirty zones of oceans, dealing with the notion of path planning for semi-autonomous unmanned vehicles. We present a hybrid cooperative architecture for unmanned aerial vehicle (UAV) to monitor ocean region and clean dirty zones with the help of swarm unmanned surface vehicles (USVs). In the path planning problem, unmanned vehicles must plan their path from the starting to the goal position. In this article, we propose a solution to handle the problem of trajectory planning for semi-autonomous cleaning vehicles. This solution is based on the proposed Genetic Algorithm (GA). In order to optimize this process, our proposed solution detects and reduces the pollution level of the ocean zones while taking into account the problem of fault tolerance related to these vehicles.
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Bella, S., Belbachir, A., Belalem, G. (2019). A Hybrid Architecture for Cooperative UAV and USV Swarm Vehicles. In: Renault, É., Mühlethaler, P., Boumerdassi, S. (eds) Machine Learning for Networking. MLN 2018. Lecture Notes in Computer Science(), vol 11407. Springer, Cham. https://doi.org/10.1007/978-3-030-19945-6_25
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DOI: https://doi.org/10.1007/978-3-030-19945-6_25
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