Điều khiển bám người đồng thời tránh vật cản cho robot di động bằng công nghệ xử lý ảnh dựa trên kỹ thuật học sâu

Abstract

Nowadays, mobile robots have been popular not only in industrial applications such as materials transportation but also in non-industrial
applications, e.g., human assistance. Among developed configurations, omnidirectional mobile robots have attracted great attention recently
due to their superior maneuverability over their conventional counterparts. In this research, an application of a four mecanum-wheeled
omnidirectional mobile robot (4-MWMR) in human assistance has been developed. By using a vision-based deep neural network in real-time,
the 4-MWMR is capable of following an authorized person, collsion avoidance and obeying the hand pose command, thereby assisting users in
transporting materials in unknown environment. Good experimental results show the ability of the developed system to be used in practice.