TY - GEN
T1 - Quality-dependent adaptation in a swarm of drones for environmental monitoring
AU - De Masi, Giulia
AU - Ferrante, Eliseo
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/2
Y1 - 2020/2
N2 - Recently, individual or groups of drones have been used increasingly more frequently for applications in environmental monitoring. Groups of drones add larger robustness, lower vulnerability, higher accuracy and flexibility with respect to the use of single drones. These groups are called swarms when designed to make collective decisions trough local mutual interactions, as real social insects swarms. Natural environments are characterized by intrinsic dynamics that are hard to predict. Since a main issue faced by swarms of drones is the absence of adaptability to changes of the environment, in this paper we proposed a principled approach that can potentially be used to develop monitoring system based on drones swarm, able to adapt to changes of the environment thanks to the presence of stubborn individuals. Furthermore, we study how the level of consensus is affected by the interplay between the proportion of stubborn individuals and the difficulty of the problem, expressed by the ratio between the qualities of the different sites.
AB - Recently, individual or groups of drones have been used increasingly more frequently for applications in environmental monitoring. Groups of drones add larger robustness, lower vulnerability, higher accuracy and flexibility with respect to the use of single drones. These groups are called swarms when designed to make collective decisions trough local mutual interactions, as real social insects swarms. Natural environments are characterized by intrinsic dynamics that are hard to predict. Since a main issue faced by swarms of drones is the absence of adaptability to changes of the environment, in this paper we proposed a principled approach that can potentially be used to develop monitoring system based on drones swarm, able to adapt to changes of the environment thanks to the presence of stubborn individuals. Furthermore, we study how the level of consensus is affected by the interplay between the proportion of stubborn individuals and the difficulty of the problem, expressed by the ratio between the qualities of the different sites.
KW - Adaptability
KW - Collective decision making
KW - Dynamic environment
KW - Monitoring
KW - Swarm
UR - http://www.scopus.com/inward/record.url?scp=85087457154&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85087457154&partnerID=8YFLogxK
U2 - 10.1109/ASET48392.2020.9118235
DO - 10.1109/ASET48392.2020.9118235
M3 - Conference contribution
AN - SCOPUS:85087457154
T3 - 2020 Advances in Science and Engineering Technology International Conferences, ASET 2020
BT - 2020 Advances in Science and Engineering Technology International Conferences, ASET 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 Advances in Science and Engineering Technology International Conferences, ASET 2020
Y2 - 4 February 2020 through 9 April 2020
ER -