Journal of Food, Agriculture and Environment




Precise spraying path planning method for Y-shaped fruit trees based on depth vision and an ant colony obstacle avoidance algorithm


Author(s):

Juan Liang, Ke Xiao,

Recieved Date: 2021-08-17, Accepted Date: 2021-09-30

Abstract:

To achieve the precise spraying of Y-shaped fruit trees, this paper combines colour images and depth images, proposes an algorithm for detecting the spraying driving range based on the extraction of edge contours and the use of algorithms for planning the optimal paths of spraying equipment based on an ant colony obstacle avoidance algorithm, and conducts precise planning for the obtained spraying driving paths. First, the colour image is segmented to divide the tree wall area (TWA) of the road and fruit trees and accurately distinguish the drivable area for the spraying equipment, and an algorithm for detecting the spraying driving range is proposed. Then, through the fusion of the depth and colour images, the edge contours of the Y-shaped fruit tree canopies are precisely fitted to form a grid map, which is then combined with the ant colony obstacle avoidance algorithm, and an optimal spraying driving path planning algorithm is proposed. Finally, the fitting curves and canopy edge contours of Y-shaped fruit trees are tested to verify the fitting performance of the algorithm. The experimental results indicate that the proposed path planning algorithm can accurately detect the fruit tree area and precisely plan the spraying path.

Keywords:

 Y-shaped fruit tree, driving range detection, optimal path planning, depth image, precise spray


Journal: Journal of Food, Agriculture and Environment
Year: 2021
Volume: 19
Issue: 3&4
Category: Agriculture
Pages: 44-53


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