A vision-based autonomous aerial spray system for precision agriculture

In the past several years, UAV has been extensively used in agriculture. However, the efficiency is still not as high as desired and the phenomenon of pesticide pollution is still existing. This is mainly because of the following two problems: 1) the autonomy of most existing UAV system is still very limited. Actually, most of them are still operated through remote-controlling. 2) the UAV's operating precision is not high enough due to the low accuracy flight control near the plants. Therefore, in 2016, the Aviation Industry Corporation of China (AVIC) has announced a UAV competition, called International Unmanned Aerial Vehicle (UAV) Innovation Grand Prix (UAVGP), to promote the technique progress of agriculture oriented UAVs. This competition mainly focuses on a typical high precise spraying mission, and in order to present the autonomy, all involved UAVs are required to operate autonomously without any human intervention. Our UAV system finally won the championship of this competition. In this paper, we present the whole system design firstly; after that, the core algorithm of task-scheduling and vision for identification and localization are given; Finally, the results of experiments and competition are introduced and analyzed in detail to show the efficiency and precision of the whole system.

[1]  Morten Bisgaard,et al.  Adaptive Surveying and Early Treatment of Crops with a Team of Autonomous Vehicles , 2011, ECMR.

[2]  Sebastian G. Elbaum,et al.  On crop height estimation with UAVs , 2014, 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[3]  Yubin Lan,et al.  Development of a PWM precision spraying controller for unmanned aerial vehicles , 2010 .

[4]  Robert E. Mahony,et al.  A Practical Visual Servo Control for an Unmanned Aerial Vehicle , 2008, IEEE Transactions on Robotics.

[5]  Yubin Lan,et al.  Development of a Spray System for an Unmanned Aerial Vehicle Platform , 2009 .

[6]  Akira Sato.  The RMAX Helicopter UAV , 2003 .

[7]  V Sazdovski,et al.  Inertial Navigation Aided by Vision-Based Simultaneous Localization and Mapping , 2011, IEEE Sensors Journal.

[8]  Fernando Santos Osório,et al.  The use of unmanned aerial vehicles and wireless sensor network in agricultural applications , 2012, 2012 IEEE International Geoscience and Remote Sensing Symposium.

[9]  Darius Burschka,et al.  Toward a Fully Autonomous UAV: Research Platform for Indoor and Outdoor Urban Search and Rescue , 2012, IEEE Robotics & Automation Magazine.

[10]  Farid Kendoul,et al.  Survey of advances in guidance, navigation, and control of unmanned rotorcraft systems , 2012, J. Field Robotics.

[11]  R. Gerhards,et al.  Practical experiences with a system for site‐specific weed control in arable crops using real‐time image analysis and GPS‐controlled patch spraying , 2006 .

[12]  Yong Zhang,et al.  Research on computer vision-based for UAV autonomous landing on a ship , 2009, Pattern Recognit. Lett..

[13]  Fernando Santos Osório,et al.  The use of unmanned aerial vehicles and wireless sensor networks for spraying pesticides , 2014, J. Syst. Archit..

[14]  Jianda Han,et al.  Development of an unmanned helicopter automatic barrels transportation system , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

[15]  Liu,et al.  Enhanced Geometric Map： a 2D＆3D Hybrid City Model of Large Scale Urban Environment for Robot Navigation , 2016 .

[16]  S. Christensen,et al.  Real‐time weed detection, decision making and patch spraying in maize, sugarbeet, winter wheat and winter barley , 2003 .

[17]  Vijay Kumar,et al.  Minimum snap trajectory generation and control for quadrotors , 2011, 2011 IEEE International Conference on Robotics and Automation.

[18]  Fei Wang,et al.  A Robust Real-Time Vision System for Autonomous Cargo Transfer by an Unmanned Helicopter , 2015, IEEE Transactions on Industrial Electronics.