Correction of the movement of the mobile robot using the modified algorithm

Abstract

Currently, automation of processes in which a robot can replace a human is widespread. To solve this problem, robots must be able to move independently from one position to another. Currently, many different approaches have been developed to solve this problem, such as neural networks, the method of potential fields, fuzzy logic methods, genetic algorithms, and computer vision. One of the most effective methods of solving the navigation problem is the method of building a navigation system based on the use of algorithms for localization, mapping, and automatic obstacle avoidance. One of the most effective obstacle avoidance algorithms is the D-star algorithm, which, despite its effectiveness, has some drawbacks. The method of potential fields and neural networks also showed good results, but each of them separately has several significant drawbacks. Based on the method of building a navigation system, the method of potential fields and neural networks, a modified method has been developed that allows a mobile robot to perform autonomous movement in an environment with obstacles. This modification eliminates some of the problems that arise when implementing the navigation system and combines the advantages of the methods used.