Algorithm for optimization of apple harvesting path and simulation

Path planning is pivotal to the working efficiency of apple harvesting robot, in order to improve the picking efficiency of harvesting robot, the algorithm for optimization of apple harvesting path was studied. In this study, path planning is translated into three dimensional Travel Salesman Problem. According to the apple position obtained through image processing, an improved ant colony algorithm was studied in the optimization of apple-picking path, which can overcome premature convergence and local convergence of the search. Three-dimensional model building and driving methods were studied. Experimental results show that when there are 250 apples, the improved ant colony algorithm can reduce alternate times to 25.3% of basic algorithm, while the total distance is 94.3%, therefore, the improved ant colony algorithm cannot only reduce algorithm times, but also can obtain better values. This study is of great importance to the optimization of apple-picking path.