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Coordination of Groups of Mobile Autonomous Agents Using Nearest Neighbor Rules
, 2002
"... In a recent Physical Review Letters paper, Vicsek et. al. propose a simple but compelling discretetime model of n autonomous agents fi.e., points or particlesg all moving in the plane with the same speed but with dierent headings. Each agent's heading is updated using a local rule based on ..."
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Cited by 613 (42 self)
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In a recent Physical Review Letters paper, Vicsek et. al. propose a simple but compelling discretetime model of n autonomous agents fi.e., points or particlesg all moving in the plane with the same speed but with dierent headings. Each agent's heading is updated using a local rule based on the average of its own heading plus the headings of its \neighbors." In their paper, Vicsek et. al. provide simulation results which demonstrate that the nearest neighbor rule they are studying can cause all agents to eventually move in the same direction despite the absence of centralized coordination and despite the fact that each agent's set of nearest neighbors change with time as the system evolves. This paper provides a theoretical explanation for this observed behavior. In addition, convergence results are derived for several other similarly inspired models.
Stable Flocking of Mobile Agents, Part II: Dynamic Topology
 In IEEE Conference on Decision and Control
, 2003
"... This is the second of a twopart paper, investigating the stability properties of a system of multiple mobile agents with double integrator dynamics. In this second part, we allow the topology of the control interconnections between the agents in the group to vary with time. Specifically, the contro ..."
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Cited by 48 (4 self)
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This is the second of a twopart paper, investigating the stability properties of a system of multiple mobile agents with double integrator dynamics. In this second part, we allow the topology of the control interconnections between the agents in the group to vary with time. Specifically, the control law of an agent depends on the state of a set of agents that are within a certain neighborhood around it. As the agents move around, this set changes giving rise to a dynamic control interconnection topology and a switching control law. This control law consists of a a combination of attractive/repulsive and alignment forces. The former ensure collision avoidance and cohesion of the group and the latter result to all agents attaining a common heading angle, exhibiting flocking motion. Despite the use of only local information and the time varying nature of agent interaction which affects the local controllers, flocking motion can still be established, as long as connectivity in the neighboring graph is maintained.
Multiagent coordination using nearestneighbor rules: revisiting the Vicsek model”; http://arxiv.org/abs/cs.MA/0407021
"... Recently Jadbabaie, Lin and Morse (IEEE Transactions on Automatic Control, 48(6):9881001, 2003.) give a mathematical analysis for the discrete time model of groups of mobile autonomous agents raised by Vicsek et al. in 1995. In their paper, Jadbabaie et al. show that all agents shall move in the sa ..."
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Cited by 16 (0 self)
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Recently Jadbabaie, Lin and Morse (IEEE Transactions on Automatic Control, 48(6):9881001, 2003.) give a mathematical analysis for the discrete time model of groups of mobile autonomous agents raised by Vicsek et al. in 1995. In their paper, Jadbabaie et al. show that all agents shall move in the same heading provided that these agents are periodically linked together. This paper sharpens this result by showing that coordination will be reached under very mild condition. This also gives an affirmative answer to one question raised by Jadbabie et al. Index Terms—Decentralized control, multiagent coordination, switched systems. 1
Flocking in Teams of Nonholonomic Agents
 Cooperative Control, Lecture Notes in Control and Information Sciences
, 2003
"... Summary. The motion of a group of nonholonomic mobile agents is synchronized using local control laws. This synchronization strategy is inspired by the early flocking model proposed by Reynolds [22] and following work [29, 8]. The control laws presented ensure that all agent headings and speeds conv ..."
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Cited by 12 (1 self)
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Summary. The motion of a group of nonholonomic mobile agents is synchronized using local control laws. This synchronization strategy is inspired by the early flocking model proposed by Reynolds [22] and following work [29, 8]. The control laws presented ensure that all agent headings and speeds converge asymptotically to the same value and collisions between the agents are avoided. The stability of this type of motion is closely related to the connectivity properties of the underlying interconnection graph. Proof techniques are based on LaSalle’s invariant principle and algebraic graph theory and the results are verified in numerical simulations. 1
An ODE Model of the Motion of Pelagic Fish
, 2007
"... A system of ordinary differential equations (ODEs) is derived from a discrete system of Vicsek, Czirók et al. [35], describing the motion of a school of fish. Classes of linear and stationary solutions of the ODEs are found and their stability explored using equivariant bifurcation theory. The exist ..."
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Cited by 8 (1 self)
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A system of ordinary differential equations (ODEs) is derived from a discrete system of Vicsek, Czirók et al. [35], describing the motion of a school of fish. Classes of linear and stationary solutions of the ODEs are found and their stability explored using equivariant bifurcation theory. The existence of periodic and toroidal solutions is also proven under deterministic perturbations and structurally stable heteroclinic connections are found. Applications of the model to the migration of the capelin, a pelagic fish that undertakes an extensive migration in the North Atlantic, are discussed and simulation of the ODEs presented. 1
Stability of Flocking Motion
, 2003
"... This paper in vestigates the aggregated stability properties of of a system of multiple mobileagen ts described by simpledynleS55 systems. Theagen ts are steered through local coordin2Sfi5 con trol laws that arise as a combin7 tion of attractive/repulsivean align2F t forces. These forces ences colli ..."
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Cited by 6 (0 self)
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This paper in vestigates the aggregated stability properties of of a system of multiple mobileagen ts described by simpledynleS55 systems. Theagen ts are steered through local coordin2Sfi5 con trol laws that arise as a combin7 tion of attractive/repulsivean align2F t forces. These forces ences collision avoidan e a n cohesion of the groupan result to all agen ts attain[S a common headin anin exhibitin flockin motion Two cases are con197 ered: in the first, position in[]5 ation from all group members is available to each agen t; in the seconc each agen t has access to position i n ormation of on( the agen ts layin in ide its n ighborhood. It is then shown that regardless ofan y arbitrary chan[1 in thenS[9 bor set, the flockinmotion remain stable aslon as the graph that describes the n ighborin relation amon the agen ts in the group is always con9 cted. 1
Coordination of Multiple Autonomous Vehicles
"... We analyze the coordinated motion of a group of nonholonomic vehicles that are controlled in a distributed fashion to exhibit flocking behavior. This behavior emerges from aggregating the control actions of all group members; it is not imposed by some centralized control scheme. Each vehicle is loca ..."
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Cited by 3 (0 self)
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We analyze the coordinated motion of a group of nonholonomic vehicles that are controlled in a distributed fashion to exhibit flocking behavior. This behavior emerges from aggregating the control actions of all group members; it is not imposed by some centralized control scheme. Each vehicle is locally controlled by a combination of a potential field force and an alignment force. The former control component ensures collision avoidance and attraction towards the group, while the latter steers each vehicle to the average heading of its `neighbors'. Eventually all vehicles attain a common heading and move in tight formation while avoiding collisions.
Birds of a Feather: Finite Size Effects and Critical Phenomena in Flock Dynamics
, 2000
"... A theory of flocking is proposed, which draws upon the physics of fluid dynamics and critical phenomena. Microscopic continuity equations describing a system of selfpropelled particles form the basis of this research. The analogy is motivated by recent theoretical attempts to model animal aggregati ..."
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A theory of flocking is proposed, which draws upon the physics of fluid dynamics and critical phenomena. Microscopic continuity equations describing a system of selfpropelled particles form the basis of this research. The analogy is motivated by recent theoretical attempts to model animal aggregation. The results of my research are contrasted with those obtained in a similar analysis by Tu and Toner [1998]. An analytic calculation of an order parameter for flocking provides a new perspective on the problem. Interesting new results, which challenge the conclusions of previous analyses, are revealed in the process. In particular, it is shown that flocks are subject to both finite size effects in restricted dimensions and orderdisorder transitions.
Flocks of Autonomous Mobile Agents 1
"... Abstract—The motion of a group of nonholonomic mobile agents is synchronized using local control laws. This synchronization strategy is inspired by the early flocking model proposed by Reynolds [17] and following work [22, 8]. The control laws presented ensure that all agent headings and speeds conv ..."
Abstract
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Abstract—The motion of a group of nonholonomic mobile agents is synchronized using local control laws. This synchronization strategy is inspired by the early flocking model proposed by Reynolds [17] and following work [22, 8]. The control laws presented ensure that all agent headings and speeds converge asymptotically to the same value and collisions between the agents are avoided. The stability of this type of motion is closely related to the connectivity properties of the underlying interconnection graph. Proof techniques are based on LaSalle’s invariant principle and algebraic graph theory and the results are verified in numerical simulations. Keywords—Cooperative control, multiagent systems, flocking motion. I.