Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6540593 | Computers and Electronics in Agriculture | 2015 | 13 Pages |
Abstract
Trees in orchards are natural landmarks providing suitable cues for mobile robot localisation as they are nominally planted in straight and parallel rows. This paper presents a novel tree trunk detection algorithm using a camera and laser scanner data fusion to enhance the detection capability. The algorithm detects the trees in the orchard and discriminates between trees and non-tree objects (e.g. posts and tree supports). The laser scanner is used to detect the edge points and determine the width of the tree trunks and non-tree objects, while the camera images are used to verify the colour and the parallel edges of the tree trunks and non-tree objects. The algorithm automatically adjusts the colour detection parameters after each test which shown to increase the detection accuracy. Experimental tests were conducted with a small robot platform in a real orchard environment to evaluate the performance of the tree trunk detection algorithm under two broad illumination conditions (sunny and cloudy). The algorithm was able to detect the tree trunks and discriminate between trees and non-tree objects with detection accuracy of 96.64% showing that the fusion of both vision and laser scanner technologies produced robust tree trunk detection.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Nagham Shalal, Tobias Low, Cheryl McCarthy, Nigel Hancock,