Digital Transformation in Animal and Agricultural Sciences
Authors: Wolfgang Pitzl (Josephinum Research) , Lukas Lachmann (Josephinum Research) , Raphael Völker (Josephinum Research) , Peter Riegler-Nurscher (Josephinum Research)
Problem weeds pose a challenge for agriculture. Robust detection of these plants
is crucial for their control and for assessing possible contamination of the crop.
Current UAV inspections are usually carried out using a fixed flight route, regardless
of the extent of weed infestation. Initial approaches of adaptive flight control
attempt to save flight distance by adapting flight altitude and route. We would
also like to investigate adaptive gimbal guidance, to find out whether this can have
a positive impact on flight paths and flight times. To this end, we developed a
pipeline between the server including the operating website and the drone. The
initial results, presented in this extended abstract, examine the functional capability
of the pipeline and different error sources for GPS accuracy of adaptive gimbal
pitches.
Keywords:
How to Cite: Pitzl, W. , Lachmann, L. , Völker, R. & Riegler-Nurscher, P. (2026) “Online adaptive path planning of UAVs for weed detection”, Proceedings of the Austrian Symposium on AI, Robotics, and Vision. 3(1).