Hawkeye: Open source framework for field surveillance
Delong Zhu, Yegui Du, Yuan Lin, Hongxiang Li, Chaoqun Wang, Xun Xu, Max Q.-H. Meng
Abstract
This paper introduces a generic framework for field surveillance using consumer rotorcrafts and ground vehicles. Building such an autonomous system comes with two key challenges in persistent perception and obstacle avoidance. We begin with explaining two core algorithms to solve the challenges: an auto-landing algorithm that enables a quadrotor to land on a moving ground vehicle at a speed of 6.00 m/s, and an obstacle avoidance algorithm that ensures the safety of the quadrotor during searching process. On the basis of these algorithms, the architecture and infrastructure of Hawkeye framework are presented as well. Hawkeye is designed to be a generic platform with extensibility that allows integration of other domain applications. We demonstrate the potential of Hawkeye framework in a simulated agriculture monitoring mission and report its performance at the end of the paper.
BibTeX
@inproceedings{iros2017_hawkeyeopensourc,
title = {Hawkeye: Open source framework for field surveillance},
author = {Delong Zhu and Yegui Du and Yuan Lin and Hongxiang Li and Chaoqun Wang and Xun Xu and Max Q.-H. Meng},
booktitle = {IROS 2017},
year = {2017}
}