  Under the background of 5G, Internet, artificial intelligence technol,ogy and
robot technology, warehousing, and logistics robot technology has developed
rapidly, and products have been widely used. A practical application is to help
warehouse personnel pick up or deliver heavy goods at dispersed locations based
on dynamic routes. However, programs that can only accept instructions or
pre-set by the system do not have more flexibility, but existing human
auto-following techniques either cannot accurately identify specific targets or
require a combination of lasers and cameras that are cumbersome and do not
accomplish obstacle avoidance well. This paper proposed an algorithm that
combines DeepSort and a width-based tracking module to track targets and use
artificial potential field local path planning to avoid obstacles. The
evaluation is performed in a self-designed flat bounded test field and
simulated in ROS. Our method achieves the SOTA results on following and
successfully reaching the end-point without hitting obstacles.
