In order to achieve accurate identification and stable tracking of specific dynamic targets

an intelligent algorithm and system based on machine vision is proposed. The system uses the Jetson TX2 as the control core

making full use of the YOLOv3 algorithm-based convolutional neural network to realize the dynamic target recognition locally. Combined with the fuzzy logic-based tracking obstacle avoidance algorithm

the target ’s steering

rotation amplitude and obstacle position are identified. It is realized that the precise control of the motion of the system and accurate avoidance for obstacle. The target recognition algorithm used in the system performs real-time local processing and feedback on the front-end video stream. After testing

the system has stable operation

high accuracy and strong real-time performance. It can be widely used in intelligent following luggage

security patrol robots and other intelligent products

with high market application value.