TY - JOUR
T1 - Multi robot distance based formation using Parallel Genetic Algorithm
AU - López-González, A.
AU - Meda Campaña, J. A.
AU - Hernández Martínez, E. G.
AU - Contro, P. Paniagua
N1 - Publisher Copyright:
© 2019 Elsevier B.V.
PY - 2020/1
Y1 - 2020/1
N2 - In this paper an alternative method to achieve distance based formation is presented. The method uses Genetic Algorithms to find a suitable solution based on angle and distance, and an appropriate constant velocity to avoid collisions. The designed algorithm is extended to a parallel scheme to improve its performance and achieve Artificial Distributed Intelligence, in which the robots share, through solution migration, the best ways to converge to desired distances while avoiding collisions, finally reaching consensus on the solution. The algorithm is tested using simulations and real robots experiments.
AB - In this paper an alternative method to achieve distance based formation is presented. The method uses Genetic Algorithms to find a suitable solution based on angle and distance, and an appropriate constant velocity to avoid collisions. The designed algorithm is extended to a parallel scheme to improve its performance and achieve Artificial Distributed Intelligence, in which the robots share, through solution migration, the best ways to converge to desired distances while avoiding collisions, finally reaching consensus on the solution. The algorithm is tested using simulations and real robots experiments.
KW - Consensus
KW - Distributed Artificial Intelligence
KW - Formation
KW - Multi robot
KW - Parallel Genetic Algorithm
UR - http://www.scopus.com/inward/record.url?scp=85075464885&partnerID=8YFLogxK
U2 - 10.1016/j.asoc.2019.105929
DO - 10.1016/j.asoc.2019.105929
M3 - Artículo
AN - SCOPUS:85075464885
SN - 1568-4946
VL - 86
JO - Applied Soft Computing Journal
JF - Applied Soft Computing Journal
M1 - 105929
ER -