TY - GEN
T1 - Flocking in stationary and non-stationary environments
T2 - 11th International Conference on Parallel Problem Solving from Nature, PPSN 2010
AU - Ferrante, Eliseo
AU - Turgut, Ali Emre
AU - Mathews, Nithin
AU - Birattari, Mauro
AU - Dorigo, Marco
PY - 2010/11/12
Y1 - 2010/11/12
N2 - We propose a novel communication strategy inspired by explicit signaling mechanisms seen in vertebrates, in order to improve performance of self-organized flocking for a swarm of mobile robots. The communication strategy is used to make the robots match each other's headings. The task of the robots is to coordinately move towards a common goal direction, which might stay fixed or change over time. We perform simulation-based experiments in which we evaluate the accuracy of flocking with respect to a given goal direction. In our settings, only some of the robots are informed about the goal direction. Experiments are conducted in stationary and non-stationary environments. In the stationary environment, the goal direction and the informed robots do not change during the experiment. In the non-stationary environment, the goal direction and the informed robots are changed over time. In both environments, the proposed strategy scales well with respect to the swarm size and is robust with respect to noise.
AB - We propose a novel communication strategy inspired by explicit signaling mechanisms seen in vertebrates, in order to improve performance of self-organized flocking for a swarm of mobile robots. The communication strategy is used to make the robots match each other's headings. The task of the robots is to coordinately move towards a common goal direction, which might stay fixed or change over time. We perform simulation-based experiments in which we evaluate the accuracy of flocking with respect to a given goal direction. In our settings, only some of the robots are informed about the goal direction. Experiments are conducted in stationary and non-stationary environments. In the stationary environment, the goal direction and the informed robots do not change during the experiment. In the non-stationary environment, the goal direction and the informed robots are changed over time. In both environments, the proposed strategy scales well with respect to the swarm size and is robust with respect to noise.
UR - http://www.scopus.com/inward/record.url?scp=78149237800&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=78149237800&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-15871-1_34
DO - 10.1007/978-3-642-15871-1_34
M3 - Conference contribution
AN - SCOPUS:78149237800
SN - 3642158706
SN - 9783642158704
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 331
EP - 340
BT - Parallel Problem Solving from Nature, PPSN XI - 11th International Conference, Proceedings
Y2 - 11 September 2010 through 15 September 2010
ER -