Affiliations: [a] Department of Computer Science, Laboratoire d’Informatique d’Oran, Université Oran 1 Ahmed Ben Bella, Oran, Algeria | [b] Mechatronics Department, Polytechnic Institute of Advanced Sciences, IPSA, Ivry-sur-Seine, France
Correspondence:
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Corresponding author: Bella Salima, Department of Computer Science, Laboratoire d’Informatique d’Oran, Université Oran 1 Ahmed Ben Bella, Oran, Algeria. E-mail: [email protected].
Abstract: This paper addresses the problem of ecological ocean pollution by using semi-autonomous unmanned vehicles. A hybrid approach for unmanned vehicles cooperation (HA-UVC) is presented for unmanned aerial vehicles (UAV) to monitor ocean regions and clean up their dirty areas with a swarm of unmanned surface vehicles (USV). Thus, the proposed HA-UVC addresses the problem of trajectory planning, where unmanned vehicles must find a trajectory from the starting position to the goal position while avoiding static obstacles. Consequently, two solutions are proposed in order to manage the trajectory planning problem for the semi-autonomous USV Swarm. The first solution is performed by a modified genetic algorithm (GA). However, the second one is achieved by a proposed Cartesian coordinate algorithm (CCA). In order to optimize the applicable performance, the proposed solutions make it possible to detect and reduce the level of pollution in ocean regions, while avoiding obstacles and failures of unmanned vehicles.
