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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 636 (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 53 (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.
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.
Weakly interacting pulses in synaptically coupled neural media
 SIAM J. Appl. Math
, 2005
"... Abstract. We use singular perturbation theory to analyze the dynamics of N weakly interacting pulses in a onedimensional synaptically coupled neuronal network. The network is modeled in terms of a nonlocal integrodifferential equation, in which the integral kernel represents the spatial distributi ..."
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Cited by 1 (0 self)
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Abstract. We use singular perturbation theory to analyze the dynamics of N weakly interacting pulses in a onedimensional synaptically coupled neuronal network. The network is modeled in terms of a nonlocal integrodifferential equation, in which the integral kernel represents the spatial distribution of synaptic weights, and the output activity of a neuron is taken to be a mean firing rate. We derive a set of N coupled ordinary differential equations (ODEs) for the dynamics of individual pulses, establishing a direct relationship between the explicit form of the pulse interactions and the structure of the longrange synaptic coupling. The system of ODEs is used to explore the existence and stability of stationary Npulses and traveling wave trains. Key words. neural networks, localized spiral patterns, traveling pulses, integrodifferential equations AMS subject classification. 92C20 DOI. 10.1137/040616371
Coordination of Distributed Autonomous Systems
, 2004
"... This thesis focuses on the analysis of emergent behaviors of a multiagent system. The ultimate aim is to synthesize complex group behaviors from simple social interactions among individuals based on simple strategies. One of the many challenges in the study of emergent behaviors of multiagent sys ..."
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Cited by 1 (0 self)
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This thesis focuses on the analysis of emergent behaviors of a multiagent system. The ultimate aim is to synthesize complex group behaviors from simple social interactions among individuals based on simple strategies. One of the many challenges in the study of emergent behaviors of multiagent systems is characterizing the local properties of each agent that will lead to global emergent behaviors. Two types of emergent behaviors are described, namely, the Multiagent Flocking Problem and the Multiagent Rendezvous Problem. In both problems, provably correct distributed local rules are proposed. In the Flocking problem, a local heading average rule was studied and convergence of the group heading to a common unspecified heading was proved using results in convergence of matrix products in Markov Chains. Replacing the word agent by a more general notion of identity naturally leads the Flocking problem to a class of network consensus problems. In the Rendezvous problem, convergence of the group positions to a common unspecified location was established using combinations of convex analysis and standard Lyapunov function approach. An asynchronous version of the Rendezvous problem was also solved by modelling the process using a suitably defined hybrid model and a procedure called Analytic Synchronization. Recent applications of the Controlled Mobility concept to wireless network in both synchronous and asynchronous settings to optimize energy consumption is briefly discussed at the end.