Research and Prospect of Intelligent Workshop AGV Path Planning Algorithm

Path planning algorithm is one of the core algorithms for automatic guided vehicle（AGV）to complete the autonomous task of intelligent workshop. The research status of grid method and Viewable method in environment modeling at home and abroad is described. The research results of traditional path search algorithms such as artificial potential field method, Dijstra algorithm and A* algorithm are analyzed and compared with intelligent algorithms such as particle swarm optimization algorithm, ant colony algorithm and genetic algorithm. The analysis finds that in the face of complex workshop environment, multi-factor influence and complex obstacles, some tasks are not completed or work overtime depending on the traditional algorithm. Therefore, starting from the algorithm improvement, in order to improve the operational efficiency and efficient obstacle avoidance of AGV, the fusion of intelligent algorithm and traditional algorithm will become the focus of research. Finally, combined with the existing problems in the current AGV path planning research, the research trend of intelligent development and integrated development is prospected. In future research, improvements in algorithm efficiency and integration with emerging technologies such as artificial intelligence can be considered.