Human following and collision avoidance control of mobile robots by vision-based deep neural network

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 in recent times 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 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