Picking Path Optimization of Agaricus bisporus Picking Robot

Abstract

The design and application of the mushroom picking robot will greatly reduce the labor cost, and it has become one of the research hotspots in the world. Therefore, we independently developed an A. bisporus (a kind of mushroom) picking robot and introduced its functional principle in this paper. At the same time, in order to improve the picking efficiency of the picking robot, a picking path optimization algorithm based on TSP model is proposed. Firstly, based on the TSP model, a picking route model for A. bisporus was established to determine the storage location of each A. bisporus. Then, an improved simulated annealing (I-SA) search algorithm is proposed to find the optimal path sequence. By improving the path initialization module, path generation module, and temperature drop module, the I-SA search algorithm can optimize the picking path in a short time. Finally, in order to improve the stability and reduce the running time of the I-SA search algorithm, a parallel optimization method for global search (“rough exploration”) and local search (“precision exploration”) is proposed. Through simulation experiments, the I-SA search algorithm can search stable and excellent path solution in a relatively short time. Through field experiments on mushroom base, the efficiency of picking A. bisporus can be improved by 14% to 18%, which verifies the effectiveness of the I-SA search algorithm.

Key Issues and Countermeasures of Machine Vision for Fruit and Vegetable Picking Robot

“…This shows that monocular vision and artificial potential field methods can improve the intelligent level of picking robot. In order to solve the problem that obstacles such as large canopy of fruit trees and pedestrians are easy to affect robot driving, Hu Guangrui team of Northwestern University of Agriculture and Forestry proposed an inter-row navigation path optimization method based on improved artificial potential field method [22]. In this method, the solid-state lidar carried by the mobile picking robot is used to obtain 3D point cloud information between orchard rows, LSM, Hough transform and RANSAC methods are used to extract the ridge line and initial path, and the improved artificial potential field method is used to optimize the path to avoid obstacles.…”

High precision scene stitching and recognition of agaricus bisporus based on depth camera

“…However, the picking process still heavily relies on manual labor [1] . Relying on manual picking not only incurs high costs but also greatly depends on workers' experience, resulting in low picking efficiency [2] . The growing environment of Agaricus bisporus is dark and humid, and the picking labor intensity is high.…”