Field coverage and weed mapping by UAV swarms

The demands from precision agriculture (PA) for high-quality information at the individual plant level require to re-think the approaches exploited to date for remote sensing as performed by unmanned aerial vehicles (UAVs). A swarm of collaborating UAVs may prove more efficient and economically viable compared to other solutions. To identify the merits and limitations of a swarm intelligence approach to remote sensing, we propose here a decentralised multi-agent system for a field coverage and weed mapping problem, which is efficient, intrinsically robust and scalable to different group sizes. The proposed solution is based on a reinforced random walk with inhibition of return, where the information available from other agents (UAVs) is exploited to bias the individual motion pattern. Experiments are performed to demonstrate the efficiency and scalability of the proposed approach under a variety of experimental conditions, accounting also for limited communication range and different routing protocols.

Publication type: 
Contributo in atti di convegno
Author or Creator: 
Albani, Dario
Nardi, Daniele
Trianni, Vito
Publisher: 
Institute of Electrical and Electronics Engineers,, New York, NY , Stati Uniti d'America
Source: 
IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 4319–4325, Vancouver, Canada, 24/09/2017, 28/09/2017
Date: 
2017
Resource Identifier: 
http://www.cnr.it/prodotto/i/386945
https://dx.doi.org/10.1109/IROS.2017.8206296
info:doi:10.1109/IROS.2017.8206296
http://www.scopus.com/record/display.url?eid=2-s2.0-85041961247&origin=inward
urn:isbn:9781538626825
Language: 
Eng
ISTC Author: 
Vito Trianni's picture
Real name: