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Monocular Vision-based Sense and Avoid of UAV Using Nonlinear Model Predictive Control

Published online by Cambridge University Press:  06 March 2019

Yizhai Zhang
Affiliation:
Research Center of Intelligent Robotics, School of Astronautics, Northwestern Polytechnical University, Xi’an, Shaanxi, 710072, China. E-mails: zhangyizhai@nwpu.edu.cn, wenhuiwang024@mail.nwpu.edu.cn
Wenhui Wang
Affiliation:
Research Center of Intelligent Robotics, School of Astronautics, Northwestern Polytechnical University, Xi’an, Shaanxi, 710072, China. E-mails: zhangyizhai@nwpu.edu.cn, wenhuiwang024@mail.nwpu.edu.cn
Panfeng Huang*
Affiliation:
Research Center of Intelligent Robotics, School of Astronautics, Northwestern Polytechnical University, Xi’an, Shaanxi, 710072, China. E-mails: zhangyizhai@nwpu.edu.cn, wenhuiwang024@mail.nwpu.edu.cn
Zainan Jiang*
Affiliation:
State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin, Heilongjiang, 150080, China
*
*Panfeng Huang and Zainan Jiang are both corresponding authors. E-mails: pfhuang@nwpu.edu.cn, jiangzainan@hit.edu.cn
*Panfeng Huang and Zainan Jiang are both corresponding authors. E-mails: pfhuang@nwpu.edu.cn, jiangzainan@hit.edu.cn

Summary

The potential use of onboard vision sensors (e.g., cameras) has long been recognized for the Sense and Avoid (SAA) of unmanned aerial vehicles (UAVs), especially for micro UAVs with limited payload capacity. However, vision-based SAA for UAVs is extremely challenging because vision sensors usually have limitations on accurate distance information measuring. In this paper, we propose a monocular vision-based UAV SAA approach. Within the approach, the host UAV can accurately and efficiently avoid a noncooperative intruder only through angle measurements and perform maneuvers for optimal tradeoff among target motion estimation, intruder avoidance, and trajectory tracking. We realize this feature by explicitly integrating a target tracking filter into a nonlinear model predictive controller. The effectiveness of the proposed approach is verified through extensive simulations.

Type
Articles
Copyright
© Cambridge University Press 2019 

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