Improving Wireless Charging Efficiency with Machine Vision and Communication for Industrial Wireless Rechargeable Sensor Networks

Abstract

Wireless charging is an important solution to prolong the lifetime of wireless sensors with limited energy. However, charging efficiency can be greatly affected by the alignment of coils which brings a non-trivial challenge to the control of the mobile charger. In this paper, we implement a wireless charging testbed based on magnetically-coupled resonant wireless power transfer (MCR-WPT). The MCR-WPT module is equipped on a mobile robot to charge wireless sensors. The vision-based wireless charging alignment (V-WCA) algorithm is proposed to use machine vision for coil alignment. Moreover, we propose to use the wireless communication capability of wireless sensors to feedback the charging power during the alignment process, and develop the communication and vision-based wireless charging alignment (CV-WCA) algorithm based on this idea. The experimental results prove that the CV- WCA algorithm is a promising solution to improve the charging efficiency in wireless rechargeable sensor networks.