Route Planning of Intelligent Agricultural Inspection Robots Based on Improved Ant Colony Algorithm

Route planning for agricultural inspection robots is an extremely complicated combination optimization problem. The traditional optimization method cannot solve the problem of agricultural robot inspection routes, which is different from the classical TSP problem. The reason is that the coordinates of the agricultural robot inspection route are not completely connected. Therefore, an improved ant colony algorithm was proposed for route planning of agricultural inspection robots. First, the initial structure of ant colony pheromone was established, and the motion matrix of the target area was obtained. The kinematic constraints of the intelligent patrol robot were set, and the robot route planning evaluation function was constructed based on the improved ant colony algorithm. Second, an intelligent inspection robot route planning algorithm was designed by calculating the inspection completion of the inspection robot. Results show that, compared with those of the traditional ant colony algorithm, the average route length of the improved ant colony algorithm is reduced by 3.45%, and the efficiency of the algorithm is improved by 22.97%. Moreover, it has better stability and convergence and achieves better results in actual inspection tasks. © 2023 School of Science, IHU. All rights reserved.