Robot Path Planning with Avoiding Obstacles in Known Environment Using Free Segments and Turning Points Algorithm

Abstract

Currently, the path planning problem is one of the most researched topics in autonomous robotics. That is why finding a safe path in a cluttered environment for a mobile robot is an important requirement for the success of any such mobile robot project. In this work, a developed algorithm based on free segments and a turning point strategy for solving the problem of robot path planning in a static environment is presented. The aim of the turning point approach is to search a safe path for the mobile robot, to make the robot moving from a starting position to a destination position without hitting obstacles. This proposed algorithm handles two different objectives which are the path safety and the path length. In addition, a robust control law which is called sliding mode control is proposed to control the stabilization of an autonomous mobile robot to track a desired trajectory. Finally, simulation results show that the developed approach is a good alternative to obtain the adequate path and demonstrate the efficiency of the proposed control law for robust tracking of the mobile robot.

An Overview of Nature-Inspired, Conventional, and Hybrid Methods of Autonomous Vehicle Path Planning

“…Hassani et al [296] aimed at obtaining safe path in complex environment for mobile robot and proposed an algorithm combining free segments and turning points algorithms. To provide stability during navigation, sliding mode control was adopted.…”

Research on path planning of robot based on adaptive ACS fused with SHAA neural network

“…Where, r represents the global pheromone volatility, Dt ij represents the pheromone increment, and L gb represents the length of the current optimal path. From equations (3) and 4, it can be seen that the increase or volatilization of pheromone is only on the global optimal path. Only in the optimal path pheromone enhancement, the purpose is to improve the convergence speed of the algorithm.…”

“…In recent years, scholars at home and abroad have conducted extensive and in-depth research on solving the robot path planning, 1 and have proposed lots of fruitful path planning methods. In Lamini et al 2 the improved genetic algorithm (GA) was used for the path planning, which had the advantages of strong robustness and implicit parallelism, but it was prone to a premature convergence; Hassani et al 3 has used the grid method to model the environment and used A* algorithm to find the optimal path. This method was a heuristic search algorithm.…”

Planejamento de Caminho Seguro com Espuma Probabilística para um Robô Móvel

“…O planejamento de caminhoé um dos principais problemas da robótica autônoma em geral e possui um papel fundamental no projeto de robô móveis (Hassani et al, 2018). Técnicas de planejamento de caminho calculam uma sequência de configurações (poses e orientações) que o robô móvel deve assumir para atingir um determinado objetivo, istoé, sair de uma configuração inicial q inicial , até uma configuração final q f inal , sem colidir com possíveis obstáculos (Svestka and Overmars, 1998).…”