TY - EJOUR
DO - 10.1007/s11721-014-0101-7
AB - In this paper, we present a distributed control strategy, enabling agents to converge onto and travel along a consensually selected curve among a class of closed planar curves. Individual agents identify the number of neighbors within a finite circular sensing range and obtain information from their neighbors through local communication. The information is then processed to update the control parameters and force the swarm to converge onto and circulate along the aforementioned planar curve. The proposed mathematical framework is based on stochastic differential equations driven by white Gaussian noise (diffusion processes). Using this framework, there is maximum probability that the swarm dynamics will be driven toward the consensual closed planar curve. In the simplest configuration where a circular consensual curve is obtained, we are able to derive an analytical expression that relates the radius of the circular formation to the agentâ€™s interaction range. Such an intimate relation is also illustrated numerically for more general curves. The agent-based control strategy is then translated into a distributed Braitenberg-inspired one. The proposed robotic control strategy is then validated by numerical simulations and by implementation on an actual robotic swarm. It can be used in applications that involve large numbers of locally interacting agents, such as traffic control, deployment of communication networks in hostile environments, or environmental monitoring.
T1 - Decentralized Self-Selection of Swarm Trajectories: From Dynamical Systems to Robotic Implementation
IS - 4
DA - 2014
AU - Sartoretti, Guillaume Adrien
AU - Hongler, Max-Olivier
AU - Elias de Oliveira, Marcelo
AU - Mondada, Francesco
JF - Swarm Intelligence
SP - 329-351
VL - 8
EP - 329-351
PB - Springer Verlag
PP - New York
ID - 202714
KW - spatio-temporal pattern
KW - distributed swarm control
KW - Brownian agents
KW - mixed canonical-dissipative dynamics
KW - mean-field approach
KW - Braitenberg control mechanism
KW - robotics experimental validation
SN - 1935-3812
UR - http://infoscience.epfl.ch/record/202714/files/art3A10.10072Fs11721-014-0101-7.pdf
ER -