2015 · 259 citations · 9 references
EngineeringAgricultural EngineeringSustainable AgricultureAerial RoboticsAgricultural RoboticsMachine VisionAgricultural ApplicationsAgricultural Machine VisionPerception For Agricultural EnvironmentsSensor Data AcquisitionAerial Crop MonitoringDrone-based Field SensingRgb-d PerceptionRgb-d ReconstructionSmart Farming SystemsUnmanned Aerial Vehicle Crop MonitoringUnmanned Aerial Vehicle Remote SensingUnmanned Aerial Vehicle Sensing
The use of drones in agriculture is becoming increasingly popular. The paper proposes a novel method to differentiate field plowing techniques using an RGB‑D sensor. The system integrates into commercial UAVs and employs two measurement algorithms to classify plowing techniques. Experimental tests demonstrate accurate classification of plowing depths.
The use of drones in agriculture is becoming more and more popular. The paper presents a novel approach to distinguish between different field's plowing techniques by means of an RGB-D sensor. The presented system can be easily integrated in commercially available Unmanned Aerial Vehicles (UAVs). In order to successfully classify the plowing techniques, two different measurement algorithms have been developed. Experimental tests show that the proposed methodology is able to provide a good classification of the field's plowing depths.
9
3D is here: Point Cloud Library (PCL)
Radu Bogdan Rusu, Steve Cousins · 2011 · 4.8K citations
Robust extended Kalman filtering
Garry Einicke, L.B. White · IEEE Transactions on Signal Processing · 1999 · 398 citations