Advance of Target Visual Information Acquisition Technology for Fresh Fruit Robotic Harvesting: A Review

文献类型： 外文期刊

第一作者： Li, Yajun

作者： Li, Yajun;Feng, Qingchun;Li, Tao;Xie, Feng;Liu, Cheng;Xiong, Zicong;Li, Yajun;Feng, Qingchun;Li, Tao;Xie, Feng;Liu, Cheng;Xiong, Zicong

作者机构：

关键词： fresh fruit; harvesting robot; visual information; stereo location

期刊名称：AGRONOMY-BASEL （ 影响因子：3.949； 五年影响因子：4.117 ）

ISSN：

年卷期： 2022 年 12 卷 6 期

页码：

收录情况： SCI

摘要： In view of the continuous increase in labor costs for complex picking tasks, there is an urgent demand for intelligent harvesting robots in the global fresh fruit cultivation industry. Fruit visual information is essential to guide robotic harvesting. However, obtaining accurate visual information about the target is critical in complex agricultural environments. The main challenges include the image color distortion under changeable natural light, occlusions from the interlaced plant organs (stems, leaves, and fruits), and the picking point location on fruits with variable shapes and poses. On top of summarizing the current status of typical fresh fruit harvesting robots, this paper outlined the state-of-the-art advance of visual information acquisition technology, including image acquisition in the natural environment, fruit recognition from the complex backgrounds, target stereo locating and measurement, and fruit search among the plants. It then analyzed existing problems and raised future potential research trends from two aspects, multiple images fusion and self-improving algorithm model.

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