Branch localization method based on the skeleton feature extraction and stereo matching for apple harvesting robot

• Main Authors: Wei Ji, Xiangli Meng, Zhijie Qian, Bo Xu, Dean Zhao
• Format: Article
• Language: English
• Published: SAGE Publishing 2017-05-01
• Series: International Journal of Advanced Robotic Systems
• Online Access: https://doi.org/10.1177/1729881417705276

Aiming at the problem of apple branch obstacle localization in fruit picking process of harvesting robot manipulator, in order to obtain three-dimensional information of the apple branch obstacle, the binocular stereo vision localization method of apple branch obstacle is proposed. Firstly, branch skeleton is extracted by morphological thinning method and then the feature skeleton is obtained after removing the false branch and recovering the occluded branch. After that, the endpoints and bifurcation points regarded as match feature points are extracted from skeleton, and the stereo matching algorithm based on features is adopted. Then, the depth information of branch obstacle is obtained on the basis of triangulation theory. Finally, the experiment results for apple tree branches localization show that the error lies in ±6.2 mm. Moreover, the error is merely ±1.5 mm when the distance between the object and the binocular camera is 1000 mm, which meets with localization accuracy requirements of apple harvesting robot visual system.