@inproceedings{5521c47d827c490e83cd18527def8bd3,
title = "Autonomous inductive charging system for battery-operated electric drones",
abstract = "Electric drones have a wide range of applications due to the convenience and agility. One of the main hurdles for their wide deployment and full automation is the battery life limitation and the need for manual intervention for charging. In this work, we present a solar powered charging system capable of automatically charging battery-powered drones in remote locations. We developed a tethered robotic rover equipped with a 2D Lidar sensor to detect and localize a drone, and a robotic arm equipped with an inductive charging pad. The charging pad senses current measurements from individual inductive coils, and adjusts accordingly the robotic arm position to maximize charging rate. Such system, in principal, can cater for arbitrary drone shapes and landing positions and is less susceptible to external lighting and environmental conditions by the use of Lidar and current sensors instead of computer vision.We remark that our system can be also applied to charging other small electric vehicles.",
keywords = "Drones, Electric Vehicles, Inductive charging, Robotics",
author = "Majid Khonji and Mohammed Alshehhi and Tseng, \{Chien Ming\} and Chau, \{Chi Kin\}",
note = "Publisher Copyright: {\textcopyright} 2017 Copyright held by the owner/author(s). Publication rights licensed to ACM.; 8th ACM International Conference on Future Energy Systems, e-Energy 2017 ; Conference date: 16-05-2017 Through 19-05-2017",
year = "2017",
month = may,
day = "16",
doi = "10.1145/3077839.3078462",
language = "British English",
series = "e-Energy 2017 - Proceedings of the 8th International Conference on Future Energy Systems",
pages = "322--327",
booktitle = "e-Energy 2017 - Proceedings of the 8th International Conference on Future Energy Systems",
}