Research on Path Planning for Robot Based on Improved Design of Non-Standard Environment Map With Ant Colony Algorithm - Feng Li; Young-Chul Kim; Ziang Lyu; Han Zhang (IEEE Access, 2023)
The maps used for the path planning of mobile robots are mostly grid maps, which are generated through independent design or sensor measurement to obtain relevant information and then modeling. To obtain the robot motion planning path more quickly, this paper proposes a method of robot motion path planning through the ant colony algorithm under a non-standard environment map. The non-standard environment map is used for standard grid design, and the grid map is optimized by the method of no safety distance added obstacle box selected and safety distance added obstacle box selected, then the path planning is carried out through the ant colony algorithm. In addition, the mutual correspondence between grid maps and real environment maps was solved by adding calibration objects. The experimental results show that this method can not only effectively solve the problem of ant colony algorithms under a non-standard real environment map, show the planning path and pose on the non-standard real environment map, moreover, the safety degree of the planning path in the real environment is also increased by 29.51%, ensuring the safety degree of the whole planning path, which improves the intelligent degree of robot motion path planning.