Robot path planning method based on rough set theory and a genetic algorithm

Rough set theory and a genetic algorithm are used in this study to solve the low efficacy and accuracy in robot path planning. For the global path planning of a mobile robot, we simplified the visibility graph, such that it would be suitable for the path planning algorithm of the mobile robot to solve the problem in environment modeling. The redundant obstacle that did not affect the result of path planning were removed by considering the positions of the obstacles in the environment and the relationship between the starting point and ending point of the mobile robot. The representation of the environment model was simplified. The purpose of reducing the number of alternative paths in the process of path planning was achieved; consequently, the efficiency of the follow-up path planning algorithm was improved. Experimental results show that the proposed method can substantially improve robot path planning.