We present an autonomous aerial system which can safely navigate inside the rows of an orchard for crop inspection, yield estimation and similar farm management tasks. Our operating environment has two practical constraints: GPS signal can be unreliable close to the ground and the trees can grow large branches that might block the robot's predetermined path. To address these challenges, we developed components for navigation, vision-based obstacle detection and avoidance and path planning for visual coverage. Results from a field demonstration in an apple orchard are presented showcasing the ability of our system to perform successful navigation and complete yield coverage of apple tree rows.
Bibliographical noteFunding Information:
This work is supported in part by NSF Awards 1111638, 1525045 and the MnDrive initiative.The authors thank Professors Emily Hoover, Cindy Tong and James Luby from the Department of Horticultural Science, University of Minnesota for access to their orchards and useful discussions.
© 2019 Elsevier B.V.
- Agricultural robotics
- Dynamic obstacle avoidance
- Unmanned aerial vehicles
- Vision-based navigation