基于视觉的采摘机器人目标识别与定位方法研究综述

目标识别和定位的精度直接关系到采摘机器人采摘效率、质量和速度。本文对近年来采摘机器人的目标识别和三维定位的研究工作进行了系统性的总结和分析,综述了果蔬识别和定位的几种主要方法:目标识别:数字图像处理技术、基于机器学习的图像分割与分类器和基于深度学习的算法;三维定位:基于单目彩色相机、基于立体视觉匹配、基于深度相机、基于激光测距仪和基于光基3D相机飞行时间的三维定位。分析了影响果蔬识别和定位精度的主要因素:光照变化、复杂的自然环境、遮挡以及动态环境干扰下成像不精确。最后对采摘机器人目标识别与定位的未来发展作了几点展望。

Vision based target recognition and location for picking robot: A review

The accuracy of target recognition and location is directly related to the picking efficiency, quality and speed of the picking robot. In this article, the research works on target recognition and three-dimensional location of the picking robot in recent years are systematically summarized and analyzed. Several main methods of fruit and vegetable recognition and location are summarized. For target recognition, the methods include digital image processing technology, machine learning image segmentation and classifier and algorithm based on deep learning. For three-dimensional location, the methods consist of monocular color camera, stereo vision matching, depth camera, laser rangefinder and optical 3D camera based on flight time. The main factors that affect the accuracy of fruit and vegetable recognition and positioning are analyzed, which include illumination change, complex natural environment, occlusion and imprecision imaging under dynamic environment interference. Finally, the future development of target recognition and location of picking robot is prospected.