Abstract: Because of the high cost of artificial fruit and vegetable picking and slow development of domestic fruit and vegetable picking robots, an intelligent robot is designed to reduce labor costs and time costs. According to the College Students’ Innovative Entrepreneurial Training Program, the design process of the fruit and vegetable piking robot is studied, using NVIDIA Jetson Nano development board to improve VI( Visual Identity) computing efficiency. The VI algorithm adopts the YOLO V5s algorithm and the motion control part to analyze the forward kinematics solution of the 5-DOF( Degree-Of-Freedom) mechanical arm, the forward kinematics formula of the 5-DOF mechanical arm is derived, and thus finding out about its activity space. In the End-Effector section, the gripper is used to facilitate the picking of various fruits and vegetables. A clearer intelligent structure for fruit and vegetable picking is established, the speed of VI is increased by more than 10 times by using NVIDIA Jetson Nano. Through the analysis of the forward kinematics formula, the End-Effector Action is more accurate, and also the fruit and vegetable picking aiming is completely realized within an acceptable deviation.

Key words: visual identity, deep learning, mechanical arm, motion control