Details

Autor(en) / Beteiligte

• Delong Zhu
• Yegui Du
• Yuan Lin
• Hongxiang Li
• Chaoqun Wang
• Xun Xu
• Meng, Max Q.-H

Titel

Hawkeye: Open source framework for field surveillance

Ist Teil von

• 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2017, p.6083-6090

Ort / Verlag

IEEE

Erscheinungsjahr

2017

Quelle

IEEE/IET Electronic Library (IEL)

Beschreibungen/Notizen

• 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.