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

Human Following Based on Visual Perception in the Context of Warehouse Logistics