Abstract
Abstract Intelligent mobile robots can take up various repetitive labor tasks instead of humans, but with the increase in labor requirements, the requirements for the autonomous working ability of intelligent mobile robots have also increased. This research used machine vision to identify obstacles in the working environment; then, a plane model was constructed for the working environment of the intelligent mobile robot with the help of machine vision. The moving path was planned by the ant colony algorithm. The robot adopted the trajectory tracking control law to track the planned path to realize the autonomous movement of the intelligent mobile robot. Finally, experiments were carried out, and the trajectory control of the robot moving on the path planned by the ant colony algorithm was compared with that planned by the genetic algorithm. The results showed that the ant colony algorithm converged faster and planned a shorter path after stability; when the coordinates of the starting and end points of the planned path were (0.0 m, 2.5 m) and (5.0 m, 0.0 m), respectively, the turning point coordinates of the paths planned by the genetic and ant colony algorithms were (2.5 m, 2.0 m) and (3.5 m, 0.0 m), respectively; the robot had shorter movement trajectory, smaller deviation, and less movement time on the path planned by the ant colony algorithm than the genetic algorithm.
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