Proposta de Planejamento Dinâmico de Navegação para Robôs Móveis Terrestres baseada em Otimização por Enxame de Partículas

Abstract

The article presents a new trajectory planning approach for mobile ground robots, named Dynamic Planning Navigation Algorithm optimized with Particle Swarm Optimization (DPNA-PSO), which utilizes the Particle Swarm Optimization (PSO) algorithm to replace the Genetic Algorithm (GA) used in the Dynamic Planning Navigation Algorithm optimized with Genetic Algorithm (DPNA-GA) strategy. Experiments conducted in various scenarios demonstrated significant improvements with DPNA-PSO, resulting in more precise and efficient displacements, smoother trajectories, and reduced oscillation during navigation. Additionally, the reduction in trajectory planning processing time contributes to a more agile response of the robot in the presence of obstacles and environmental changes. These enhancements underscore the promising potential of DPNA-PSO to enhance autonomous navigation of ground mobile robots, thereby enhancing safety and operational efficiency. Based on these promising results, it is suggested to explore the application of DPNA-PSO in more complex environments and with various types of mobile robots to validate its effectiveness and adaptability.