AN OBSTACLE DETECTION SYSTEM BASED ON MONOCULAR VISION FOR APPLE ORCHARD ROBOT

被引：6

作者：

Zhang, Jianfeng ^{[1
]}

Yang, Bin ^{[1
]}

Geng, Nan ^{[1
]}

Huang, Lvwen ^{[1
]}

机构：

[1] Northwest A&F Univ, Coll Informat Engn, Yangling 712100, Peoples R China

来源：

INTERNATIONAL JOURNAL OF ROBOTICS & AUTOMATION | 2017年 / 32卷 / 06期

关键词：

Apple orchard robot; obstacle detection; monocular vision; inverse perspective transformation; NEURAL-NETWORK; EXTRACTION;

D O I：

10.2316/Journal.206.2017.6.206-5036

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Obstacle detection is one of the key problems in the autonomous movement of intelligent mobile robot. This paper focuses on the study of obstacle detection in the complex apple orchard. First, using L* a* b* (colour space for non-self-illuminated, named by CIE 1976 L* a* b* or CIELAB) colour model to represent the apple orchard image, the obstacles in the robot's walking area can be effectively segmented from the complex background by one-dimensional fuzzy entropy image segmentation algorithm. Then, the coordinate of the point close to the robot of the obstacle is obtained. Finally, the distance between the robot and the obstacle is estimated using the inverse perspective transformation. The experimental results show that the maximum absolute error is 7.87 cm and the maximum relative error is 6.53%. The results can meet the accuracy requirements of the intelligent mobile application for an apple orchard robot.

引用

页码：639 / 648

页数：10

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