Development of a Model for Generating Trajectories for an Autonomous Naval Vehicle Using Genetic Algorithms in Matlab - Oddershede-Herrera, A; Montt-Veas, C; Olivares-Chiappa, V; Quezada-Valenzuela, F; Vargas-Guzman, M; Quezada-Llanca, L (Agora University, 2024)
This work presents the development of a model for generating trajectories for an autonomous naval vehicle using genetic algorithms implemented in MATLAB. The primary objective is to optimize the routes the vehicle must follow, minimizing the traveled distance and ensuring efficient navigation. Various scenarios were tested by varying model parameters such as the number of environmental control points, the number of generations, and the number of individuals to evaluate the genetic algorithm’s performance. In each scenario, results were analyzed in terms of minimum traveled distance and the optimal sequence of trajectory points (FITNESS). The results show that the genetic algorithm can find efficient solutions, adapting to different configurations of points and generations. Specific examples illustrate the optimal generated trajectories, accompanied by graphical representations visualizing the sequence of points. This study demonstrates the effectiveness of genetic algorithms in route planning for autonomous naval vehicles and provides a solid foundation for future research and applications in autonomous navigation. © 2024 by the authors.
Keywords: Matlab; TSP; Genetic Algorithm; Cluster; Autonomous Naval Vehicle