Pourtaheri, Z. K.. (1403). Design and Stability Analysis of a Novel Path Planner for Autonomous Underwater Vehicles. فناوری آموزش, 13(1), 1-12. doi: 10.22061/jecei.2024.10624.725
Z. K. Pourtaheri. "Design and Stability Analysis of a Novel Path Planner for Autonomous Underwater Vehicles". فناوری آموزش, 13, 1, 1403, 1-12. doi: 10.22061/jecei.2024.10624.725
Pourtaheri, Z. K.. (1403). 'Design and Stability Analysis of a Novel Path Planner for Autonomous Underwater Vehicles', فناوری آموزش, 13(1), pp. 1-12. doi: 10.22061/jecei.2024.10624.725
Pourtaheri, Z. K.. Design and Stability Analysis of a Novel Path Planner for Autonomous Underwater Vehicles. فناوری آموزش, 1403; 13(1): 1-12. doi: 10.22061/jecei.2024.10624.725
Department of Mechatronics, Higher Education Complex of Bam, Bam, Iran.
تاریخ دریافت: 05 اردیبهشت 1403،
تاریخ بازنگری: 08 مرداد 1403،
تاریخ پذیرش: 16 مرداد 1403
چکیده
Background and Objectives: According to this fact that a typical autonomous underwater vehicle consumes energy for rotating, smoothing the path in the process of path planning will be especially important. Moreover, given the inherent randomness of heuristic algorithms, stability analysis of heuristic path planners assumes paramount importance. Methods: The novelty of this paper is to provide an optimal and smooth path for autonomous underwater vehicles in two steps by using two heuristic optimization algorithms called Inclined Planes system Optimization algorithm and genetic algorithm; after finding the optimal path by Inclined Planes system Optimization algorithm in the first step, the genetic algorithm is employed to smooth the path in the second step. Another novelty of this paper is the stability analysis of the proposed heuristic path planner according to the stochastic nature of these algorithms. In this way, a two-level factorial design is employed to attain the stability goals of this research. Results: Utilizing a Genetic algorithm in the second step of path planning offers two advantages; it smooths the initially discovered path, which not only reduces the energy consumption of the autonomous underwater vehicle but also shortens the path length compared to the one obtained by the Inclined Planes system optimization algorithm. Moreover, stability analysis helps identify important factors and their interactions within the defined objective function. Conclusion: This proposed hybrid method has implemented for three different maps; 36.77%, 48.77%, and 50.17% improvements in the length of the path are observed in the three supposed maps while smoothing the path helps robots to save energy. These results confirm the advantage of the proposed process for finding optimal and smooth paths for autonomous underwater vehicles. Due to the stability results, one can discover the magnitude and direction of important factors and the regression model.
