Abstract: For citrus picking, the hardware platform of picking robot composed of the upper computer, RealSense R200 depth Camera, VS-6556 vertical multijoint industrial manipulator and threefinger flexible paw was constructed. Windows10 as the development environment, librealsense camera software development kit, OpenCV computer vision library, TensorFlowGPU and Keras deep learning framework, ORIN2 manipulator control software development kit, Arduino IDE function library and SerialPort serial communication software development kit were adopted. The program design of picking control system based on depth camera and secondary development of mechanical arm included the module program design of visual identification and positioning, hand claw motion control, mechanical arm motion control and picking control. The pick control system citrus positioning and citrus picking experiment was conducted under the condition of random arrangement of citrus in the laboratory environment. The test result showed that the average positioning accuracy error of visual identification module was 1.22cm, in the process of picking oranges to identify the success rate of 100%, the average recognition time was about 47ms, citrus picking robot the success rate of 80%, the average picking time was about 15.2s. The test result verified the feasibility of the platform control system program of the picking robot, and showed that the control system could correctly and efficiently complete the whole citrus picking process.

Key words: picking robot, citrus picking, control system, program design, machine vision

摘要： 面向柑橘采摘，构建以上位机、RealSense Camera R200深度相机、VS-6556垂直多关节工业用机械臂、三指柔性手爪等组成的采摘机器人硬件平台。以Windows10为开发环境，采用librealsense相机软件开发工具包、OpenCV计算机视觉库、TensorFlowGPU和Keras深度学习框架、ORIN2机械臂控制软件开发工具包、Arduino IDE函数库以及SerialPort串口通信软件开发工具包等，研究基于深度相机、机械臂二次开发的采摘控制系统设计，包括视觉识别定位、手爪动作控制、机械臂运动控制以及采摘控制等模块的程序设计。采摘控制系统柑橘定位试验和柑橘采摘试验的测试结果显示，在实验室环境下面对随机布置的柑橘，视觉识别定位模块的平均定位精度误差为1.22cm，采摘过程中柑橘识别成功率达到100%，平均识别时间约为47ms，机器人柑橘采摘成功率达到80%，平均采摘时间约为15.2s，验证了采摘机器人平台控制系统程序的可行性，表明所开发的采摘控制系统能够正确、高效地完成整个柑橘采摘作业流程。

关键词: 采摘机器人, 柑橘采摘, 控制系统, 程序设计, 机器视觉