Research Article
Field Coverage for Weed Mapping: Toward Experiments with a UAV Swarm
@INPROCEEDINGS{10.1007/978-3-030-24202-2_10, author={Dario Albani and Tiziano Manoni and Arikhan Arik and Daniele Nardi and Vito Trianni}, title={Field Coverage for Weed Mapping: Toward Experiments with a UAV Swarm}, proceedings={Bio-inspired Information and Communication Technologies. 11th EAI International Conference, BICT 2019, Pittsburgh, PA, USA, March 13--14, 2019, Proceedings}, proceedings_a={BICT}, year={2019}, month={7}, keywords={}, doi={10.1007/978-3-030-24202-2_10} }- Dario Albani
Tiziano Manoni
Arikhan Arik
Daniele Nardi
Vito Trianni
Year: 2019
Field Coverage for Weed Mapping: Toward Experiments with a UAV Swarm
BICT
Springer
DOI: 10.1007/978-3-030-24202-2_10
Abstract
Precision agriculture represents a very promising domain for swarm robotics, as it deals with expansive fields and tasks that can be parallelised and executed with a collaborative approach. Weed monitoring and mapping is one such problem, and solutions have been proposed that exploit swarms of unmanned aerial vehicles (UAVs). With this paper, we move one step forward towards the deployment of UAV swarms in the field. We present the implementation of a collective behaviour for weed monitoring and mapping, which takes into account all the processes to be run onboard, including machine vision and collision avoidance. We present simulation results to evaluate the efficiency of the proposed system once that such processes are considered, and we also run hardware-in-the-loop simulations which provide a precise profiling of all the system components, a necessary step before final deployment in the field.
