Real environment obstacle circular edge expansion design robot path planning based on ant colony algorithm

With the development of artificial intelligence, mobile robot motion control technology is facing the key problem of intelligent path planning. The combination of a grid map and an artificial intelligence algorithm provides an effective solution for path planning. However, the current grid map generation mainly relies on laser and ultrasonic sensors to obtain environmental information for grid map modeling, which is time-consuming and laborious. To address this issue, this paper investigates a method to transform a non-standard real environment map into a standard grid map. The non-standard real environment map was processed, and the size and shape of the map were standardized. The obstacles in the map were designed as a circle; the edge was expanded to add safety distance. The experimental results show that the method can transform real environment photos into standard grid maps suitable for robot path planning, and the path planning and motion control of robots in real environments can be carried out by using this method.