Field Coverage for Weed Mapping: Toward Experiments with a UAV Swarm
| Autor: | Tiziano Manoni, Daniele Nardi, Arikhan Arik, Dario Albani, Vito Trianni |
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| Rok vydání: | 2019 |
| Předmět: |
Exploit
Robots Robotics Robot swarms Computer science Machine vision Real-time computing Swarm robotics Swarm behaviour ComputerApplications_COMPUTERSINOTHERSYSTEMS Computer Science::Multiagent Systems Computer Science::Robotics Software deployment Profiling (information science) Precision agriculture Weed |
| Zdroj: | Bio-inspired Information and Communication Technologies ISBN: 9783030242015 BICT |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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