Research on the Safety of AGV Path Planning Based on D* Algorithm

Automated Guided Vehicles are widely used in the construction of smart factories. Path planning and obstacle avoidance algorithms of automatic guided vehicles are the key technologies to realize autonomous navigation of automatic guided vehicles, which determines whether automatic guided vehicles can complete tasks efficiently and safely in complex environments. Aiming at the shortcomings of path planning of automatic guided vehicles, this paper is in order to improve their safety and stability. In this paper, the path planning algorithm of the automatic guided vehicle is optimized by using the intelligent unmanned vehicle motion planning method. Firstly, DBSC-LF algorithm is used to process the map convex, which greatly simplifies the complex terrain of the working space. Secondly, the D-star algorithm is selected as the global path planning algorithm for automatic guided vehicle path planning, and the dynamic window method is used for local path planning, and the path optimization is further carried out in obstacle avoidance. After code optimization, MATLAB simulation experiment is carried out, and the verification results are obtained and the conclusion is drawn: the improved D-star algorithm in this paper plays a significant role in improving the safety and stability of automatic guided vehicle path planning.