Neighborhood-Search-Based Path Planning Algorithm Applied to a Python Robotic Simulation Environment - Trentini, Polliana Barelli; Silva, Mateus Coelho (Anais do Workshop Latinoamericano de Dependabilidade e Segurança em Sistemas Veiculares (SSV); 2025: Anais do II Workshop Latinoamericano de Dependabilidade e Segurança em Sistemas Veiculares, 2025)
Path planning has become one of the most important fields for mobile robots. It involves analyzing various parameters, including energy consumption, movement smoothness, travel time, and collision avoidance. However, to test these path planning algorithms, researchers are often limited by the need to use 3D simulators. In this context, our work focuses on developing a path planning algorithm with a neighborhood-search-based approach using a lightweight, user-friendly framework software based on Python. This conventional approach, combined with a simulator, allowed us to test our algorithm on different maps, finding successful paths between our initial and goal points, especially on simpler maps with fewer obstacles. The methodology was evaluated in several experiments using different parameters as intermediate points and noise force for disturbances. Our results indicate the feasibility of the proposed technique, which generated valid paths and optimized them towards better solutions.