【作者】 韩非；

【导师】 郭艳玲； 齐英杰；

【作者基本信息】 东北林业大学 ， 机械设计及理论， 2011， 博士

【摘要】 蓝莓采摘机器人是一种能够在野外和林区连续、实时进行蓝莓采摘的智能机器人系统,其研究涉及多个学科的理论与技术,体现了林业现代化的最新成果,具有重要的研究意义和应用价值,受到了世界各国的重视。视觉引导下与采摘机械臂的定位是蓝莓采摘机器人研究的重要关键技术之一。视觉系统的主要功能是对蓝莓的检测识别与定位,从而确定采摘机械系统的路径规划,实现采摘机器人的智能化操作。立体视觉系统是一种被动式的传感方式,具有获取的有用信息丰富、价格低廉、质量可靠等优点。本论文旨在对蓝莓采摘机器人的基于双目视觉系统的立体视觉检测及定位系统进行研究。立体视觉系统的精确定位是立体视觉系统研究的基础。与实验室环境不同,蓝莓采摘机器人的主要应用背景为林区和野外,所以要求摄像机的定标过程应快速、精确,且必须是在线标定。围绕这个中心,本文提出一种快速精确的定标方案,该方案环境适应性强,只需要在车辆手臂任意位置处标记几个点,让手臂在视觉系统中运动几个位置,即可完成整个在线标定工作。与传统方法相比,本文提出的方法具有操作简单,精度高等优点。本文对于立体匹配及手眼标定等算法进行了深入研究。立体匹配以提高实时性和精度为目标,利用反向投影方法实现了机器人视觉系统的快速匹配。本文提出的方法在定性、定量分析效果上都优于传统模板匹配方法。通过立体定位的实验研究与验证,实现了将手眼定标系统与立体定位的协调统一。根据蓝莓采摘机器人对立体视觉系统的计算量、智能化水平、实时性要求,本文提出了基于视觉信息的蓝莓检测方法。包括基于颜色信息结合人工神经元网络模型的蓝莓分割方法和基于形状信息的蓝莓检测方法,并进行了实验验证。阐述了利用视觉技术,采用矩描述方法,根据蓝莓形状及尺寸进行蓝莓分级研究及实验验证。通过综合实验表明,本文提出的基于视觉系统的蓝莓检测、定位及分级方法具有较高的实用和理论价值。更多还原

【Abstract】 Blueberry picker is an intelligent robot, which can run autonomously and continuously on outside and hills. Its research, which involves theories and technologies of many aspects, and embodies the latest achievements of information and artificial intelligence, is of great value in research and application. In recent years, all fruit pickers and harvest robots in agriculture and forestry have received great attention all over the world. Among all the blueberry harvesting technologies, vision-based blueberry detection and positioning are the main challenges. The key problems of the blueberry picker are the rapid detection and positioning of the blueberry. Compared with other approaches, stereo vision system is a passive sensor, which does not emit light and radiation. And stereo vision system has many advantages such as cheap, accurate, and can acquire rich information.The thesis aims at the study of blueberry detection and positioning based on the stereo vision system. The basic problem for stereo vision system is the accurate calibration of the cameras. Different from that in the laboratory environment, the calibration for blueberry picker must be done quickly and accurately as the cameras are mounted on the robot, and the work space of the robot is the outside and many should be in the forestry, therefore the calibration procedure should be flexible enough. In the system that we have implemented, a flexible technique has been used to easily calibrate a camera. It is well suited for use without specialized knowledge of computer geometry. The calibration technique only requires the camera to observe some ticked points on the arm. While the arm is moving, a serial of points can be acquired. The test results show that the proposed method is valid.The stereo matching problem and hand-eye calibration system are discussed in detail in this thesis. And this thesis has done deep research in stereo matching. An inverse stereo matching method is proposed to realize the stereo matching, and the method is better on the effects of the qualitative and quantitative analysis than the traditional template matching method. Through the experimental study of three-dimensional localization and verification, the onboard calibration system and stereotactic hand-eye coordination unity is realized.According to the demands of the amount of calculation, intelligent level, real time requirement, which asked by the stereo vision system of the blueberry picker, a new blueberry detection method s are proposed based on vision information, including the blueberry segmentation method of the artificial neural network model based on the color information and the method based on the shape information, and they were validated by experiments. A grading method according to the size and shape of blueberry is discussed and experiment based on visual technology and torque description method.The comprehensive experiments show the blueberries detection, positioning and classification methods based on visual system have high practical and theoretical value.更多还原