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.

Field coverage for weed mapping: Toward experiments with a UAV swarm / Albani, D.; Manoni, T.; Arik, A.; Nardi, D.; Trianni, V.. - 289:(2019), pp. 132-146. (Intervento presentato al convegno 11th International Conference on Bio-inspired Information and Communications Technologies, BICT 2019 tenutosi a Pittsburgh; United States) [10.1007/978-3-030-24202-2_10].

Field coverage for weed mapping: Toward experiments with a UAV swarm

Manoni T.;Arik A.;Nardi D.;
2019

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.
2019
11th International Conference on Bio-inspired Information and Communications Technologies, BICT 2019
Robots; Robotics; Robot swarms
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Field coverage for weed mapping: Toward experiments with a UAV swarm / Albani, D.; Manoni, T.; Arik, A.; Nardi, D.; Trianni, V.. - 289:(2019), pp. 132-146. (Intervento presentato al convegno 11th International Conference on Bio-inspired Information and Communications Technologies, BICT 2019 tenutosi a Pittsburgh; United States) [10.1007/978-3-030-24202-2_10].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1382411
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