Oscillator Models and Collective Motion

By Derek A. Paley, N. Leonard, Rodolphe Sepulchre, Daniel Grünbaum, J. Parrish. IEEE Control Systems, 2007

257 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/57b5bcc35c8f298ff93f97cb3c7c24eca0f14746

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Citations in the corpus

On collision-avoiding initial configurations to Cucker-Smale type flocking models (2012, background): “Recently several mathematical models for such self-organized phenomena have received lots of attention due to their engineering applications such as sensor networks, and formation control of robot and unmanned aerial vehicles [26, 28, 30].”
Emergent dynamics of the Cucker-Smale flocking model and its variants (2016, background): “[6, 64], and they have been extensively studied recently because of their possible applications to sensor networks, controls of robots and unmanned aerial vehicles [49, 55, 57], and opinion formation of social networks.”
On the Characterization of Local Nash Equilibria in Continuous Games (2014, background): “The form of the cost is derived from the Laplacian potential function [19].”
Collective Motion From Consensus With Cartesian Coordinate Coupling (2008, background): “We also explicitly show the critical value for the Euler angle when there is Cartesian coordinate coupling and quantitatively characterize the re- sulting collective motions, namely, rendezvous, circular pat- terns, and logarithmic spiral patterns.”
Cooperative Robot Control and Concurrent Synchronization of Lagrangian Systems (2007, background): “One recent work [ 31 ] presented a framework called particles with coupled oscillator dynamics so that collective spatial patterns emerge.”
Distributed Control of Robotic Networks: A Mathematical Approach to Motion Coordination Algorithms (2009, background): “Regarding distributed motion coordination algorithms, much progress has been made on collective pattern formation (Suzuki and Yamashita, 1999; Belta and Kumar, 2004; Justh and Krishnaprasad, 2004; Sepulchre et al., 2007; Paley et al., 2007; Yang et al., 2008), flocking (Olfati-Saber, 2006; Lee and S”
Synchronization in complex networks of phase oscillators: A survey (2014, background): “…" or " balanced " heading angles for K = ±1, and translational motion for ω0(t) = 0, respectively circular motion for ω0(t) = 1. phase dynamics (7) give rise to elegant and useful coordination patterns that mimic animal flocking behavior (Leonard et al., 2012) and fish schools (Paley et al., 2007).”
Distributed Control of Robotic Networks (2009, background): “Regarding distributed motion coordination algorithms, much progress has been made on collective pattern formation (Suzuki and Yamashita, 1999; Belta and Kumar, 2004; Justh and Krishnaprasad, 2004; Sepulchre et al., 2007; Paley et al., 2007; Yang et al., 2008), flocking (Olfati-Saber, 2006; Lee and S”