Formations of vehicles in cyclic pursuit

By Joshua A. Marshall, Mireille E. Broucke, Bruce A. Francis. IEEE Transactions on Automatic Control, 2004

701 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/596585dca727785af96f396193df039264c3e158

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Citations in the corpus

Cooperative control for target-capturing task based on a cyclic pursuit strategy (2007, background): “On the other hand, the formation control strategies for multiagent systems under cyclic pursuit have recently been investigated (see e.g., Lin, Broucke, & Francis, 2004; Marshall et al., 2004, 2006; Sinha & Ghose, 2005 and the references therein).”
Coordination and Consensus of Networked Agents with Noisy Measurements: Stochastic Algorithms and Asymptotic Behavior (2009, background): “In fact, many symmetric models have arisen in practical applications including platoons of vehicles, robot teams, unicycle pursuit models [30, 29], cooperative sensor network deployment for tracking [1] or sampling [25], and consensus problems [9].”
On robust control algorithms for nonlinear network consensus protocols (2008, background): “control, rendezvous, flocking, cyclic pursuit, cohesion, separation, alignment, and consensus need to be developed [1–8].”
Optimal sensor placement and motion coordination for target tracking (2006, methodology): “Our proposed control algorithms are in the same spirit of those of cyclic pursuit [7, 14], flocking [6], and coverage control [4].”
Motion Coordination with Distributed Information (2007, unknown): “Among the analysis methods used, we roughly distinguish between linear techniques (ergodic, stochastic [16] and circulant matrices [31] from matrix analysis, graph Laplacians and algebraic connectivity [16, 33] from algebraic graph theory) and nonlinear techniques (symmetries of diﬀerential…”
Decentralized policies for geometric pattern formation (2007, methodology): “Lin et al. [8] exploited cyclic pursuit to achieve alignment among agents, while Marshall et al. in [9] and in [10] extended the classic cyclic pursuit to a system of wheeled vehicles, each subject to a single non-This work was supported in part by the National Science Foundation, under grant no.”
Information consensus in multivehicle cooperative control (2007, methodology): “In addition, the simplified pursuit strategy for wheeled-vehicle formations in [63] can be considered a special case of the continuous consensus algorithm (1), where the communication topology is a unidirectional ring.”
Stabilisation of infinitesimally rigid formations of multi-robot networks (2009, methodology): “Many different techniques have been used to solve this problem, for example, cyclic pursuit (Marshall, Broucke and Francis 2004) and the circumcentre law (Corte´s, Martı´nez and Bullo 2004a).”
Multi-Agent Coordination by Decentralized Estimation and Control (2008, background): “problems of bringing agents to a common meeting point, or rendezvous [7], [22], and to various types of flocking and formation control [17], [24], [37].”
Unicycle Coverage Control Via Hybrid Modeling (2010, background): “References include collision avoidance [15], cyclic pursuit [16], [17],”
Collective Motion From Consensus With Cartesian Coordinate Coupling (2008, background): “studied for single-integrator kinematics in [2], [3] while for wheeled vehicles subject to nonholonomic constraints in [4], [5].”
Backstepping control design for motion coordination of self‐propelled vehicles in a flowfield (2011, background): “Research in motion coordination of autonomous vehicles is directly applicable to a number of defense and environmental scenarios, including surveillance [4, 6, 11], wind and temperature measurement for climate monitoring [19], and modeling collective behavior of biological systems [15].”