Thèses de Doctorat et Mémoires de Magister
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Item Energy-aware USVs path planning(Université M'Hamed Bougara : Faculté de Technologie, 2022) Ouelmokhtar, Hand; Benazzouz, Djamel(Directeur de thèse)Unmanned Surface Vehicles (USV) are an innovative solution for various maritime applications such as marine navigation, rescue, environmental monitoring and surveillance, etc. USVs offer the advantage to operate in hostile or dangerous environments where humans cannot safely or not at all perform. In general, USVs operate in harsh environmental conditions that require accuracy, reliability and autonomy. To meet these critical requirements, the focus on USVs and their applications is gradually performed. One of the most important problems to be solved is that of trajectory planning. In order to execute the planned tasks, the USVs must operate in an autonomous way and manage their resources optimally in order to minimize human interventions. Thus, performance and autonomy criteria are very important to consider when executing any type of task. In this thesis, we address the general problem of maritime surveillance using a USV equipped with an on-board LiDAR (Light Detection and Ranging) that allows remote coverage of distant points. The objectives are to cover the maximum area with lowest energy cost while avoiding collisions with obstacles. To solve this problem, we used two optimization approaches: • The first one consists in using heuristic methods based on multi-objective evolutionary algorithms. In this case, two algorithms are used and compared. One consists of a local search method known as Pareto Archived Evolution Strategy (PAES). Other consists of a population-based search algorithm called Non-Dominated Genetic Sorting Algorithm II (NSGA-II). • A novel method is proposed to improve the performance of evolutionary algorithms when solving path planning problems by reducing the size of chromosomes. • The second approach isbased on the exact method using a Mixed Integer Programming (MIP) model with two objective functions inspired by both the Covering Salesman Problem (CSP) and the Travelling Salesman Problem with Profit (TSPP).Item Energy consumption modelling of marine drones and the integration of the model into ROS-based simulation(Université M'Hamed Bougara : Faculté de Technologie, 2021) Touzout, Walid; Benazzouz, Djamel(Directeur de thèse)The Unmanned Surface Vehicles (USVs) are promising solutions for various marine applications such as: maritime navigation, rescue, environmental control, military missions, oceanic maps production, etc. The main advantage of USVs is the ability to execute their functionalities in environments where humans are not able to intervene safely, in addition to their cost and continuous activity. Generally, USVs operate in difficult environmental conditions requiring precision, reliability, and autonomy. To meet these critical requirements, the scientific community is increasingly focusing its research in the USV’s field and their applications. Accordingly, one of the most difficult issues to be resolved in this field is the autonomy and energy limitation problems. Estimating and managing the power consumption of USVs is an important issue to deal with energy minimization techniques such as trajectory planning, task scheduling and optimal design of controllers. In this thesis, we present the energy consumption parameter of USVs into Robot Operating System (ROS) - based simulation through the following contributions: • An analytical model of the energy consumption of differential drive Unmanned Surface Vehicles is developed based on a three-degrees-of-freedom dynamic model of surface vessels. • A reverse engineering approach is proposed allowing the identification of the developed dynamic model’s coefficients and parameters based on a set of scenarios run within the simulation environment presented in [1]. The identified model is used in the development of the consumption model of surface vehicles. • The simulator engine is enriched with power modelling and simulation tools, so that the power consumed by the USV is instantaneously calculated, processed, and returned; thus, the energy required to accomplish a given predefined scenario is available as a new simulation result