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559
Social Potential Fields: A Distributed Behavioral Control for Autonomous Robots
, 1999
"... A Very Large Scale Robotic (VLSR) system may consist of from hundreds to perhaps tens of thousands or more autonomous robots. The costs of robots are going down, and the robots are getting more compact, more capable, and more flexible. Hence, in the near future, we expect to see many industrial and ..."
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Cited by 179 (1 self)
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A Very Large Scale Robotic (VLSR) system may consist of from hundreds to perhaps tens of thousands or more autonomous robots. The costs of robots are going down, and the robots are getting more compact, more capable, and more flexible. Hence, in the near future, we expect to see many industrial and military applications of VLSR systems in tasks such as assembling, transporting, hazardous inspection, patrolling, guarding and attacking. In this paper, we propose a new approach for distributed autonomous control of VLSR systems. We define simple artificial force laws between pairs of robots or robot groups. The force laws are inversepower force laws, incorporating both attraction and repulsion. The force laws can be distinct and to some degree they reflect the 'social relations' among robots. Therefore we call our method social potential fields. An individual robot's motion is controlled by the resultant artificial force imposed by other robots and other components of the system. The approach is distributed in that the force calculations and motion control can be done in an asynchronous and distributed manner. We also extend the social potential fields model to use spring laws as force laws. This paper presents the first and a preliminary study on applying potential fields to distributed autonomous multirobot control. We describe the generic framework of our social potential fields method. We show with computer simulations that the method can yield interesting and useful behaviors among robots, and we give examples of possible industrial and military applications. We also identify theoretical problems for future studies. 1999 Published by Elsevier Science B.V. All rights reserved.
A Survey of Consensus Problems in Multiagent Coordination
, 2005
"... As a distributed solution to multiagent coordination, consensus or agreement problems have been studied extensively in the literature. This paper provides a survey of consensus problems in multiagent cooperative control with the goal of promoting research in this area. Theoretical results regard ..."
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Cited by 148 (3 self)
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As a distributed solution to multiagent coordination, consensus or agreement problems have been studied extensively in the literature. This paper provides a survey of consensus problems in multiagent cooperative control with the goal of promoting research in this area. Theoretical results regarding consensus seeking under both timeinvariant and dynamically changing information exchange topologies are summarized. Applications of consensus protocols to multiagent coordination are investigated. Future research directions and open problems are also proposed.
Distributed consensus algorithms in sensor networks with communication channel noise and random link failures
 in Proc. 41st Asilomar Conf. Signals, Systems, Computers
, 2007
"... Abstract—The paper studies average consensus with random topologies (intermittent links) and noisy channels. Consensus with noise in the network links leads to the biasvariance dilemma—running consensus for long reduces the bias of the final average estimate but increases its variance. We present t ..."
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Cited by 146 (22 self)
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Abstract—The paper studies average consensus with random topologies (intermittent links) and noisy channels. Consensus with noise in the network links leads to the biasvariance dilemma—running consensus for long reduces the bias of the final average estimate but increases its variance. We present two different compromises to this tradeoff: the algorithm modifies conventional consensus by forcing the weights to satisfy a persistence condition (slowly decaying to zero;) and the algorithm where the weights are constant but consensus is run for a fixed number of iterations, then it is restarted and rerun for a total of runs, and at the end averages the final states of the runs (Monte Carlo averaging). We use controlled Markov processes and stochastic approximation arguments to prove almost sure convergence of to a finite consensus limit and compute explicitly the mean square error (mse) (variance) of the consensus limit. We show that represents the best of both worlds—zero bias and low variance—at the cost of a slow convergence rate; rescaling the weights balances the variance versus the rate of bias reduction (convergence rate). In contrast, , because of its constant weights, converges fast but presents a different biasvariance tradeoff. For the same number of iterations, shorter runs (smaller) lead to high bias but smaller variance (larger number of runs to average over.) For a static nonrandom network with Gaussian noise, we compute the optimal gain for to reach in the shortest number of iterations, with high probability (1), ()consensus ( residual bias). Our results hold under fairly general assumptions on the random link failures and communication noise. Index Terms—Additive noise, consensus, sensor networks, stochastic approximation, random topology. I.
Realistic modeling and rendering of plant ecosystems
 SCIENTIFIC VISUALIZATION LABORATORY, DEPARTMENT OF COMPUTER SCIENCE, TEXAS A&M UNIVERSITY, COLLEGE STATION, TX 778433112
, 1998
"... ..."
Formations of vehicles in cyclic pursuit
 IEEE TRANSACTIONS ON AUTOMATIC CONTROL
, 2004
"... Inspired by the socalled “bugs” problem from mathematics, we study the geometric formations of multivehicle systems under cyclic pursuit. First, we introduce the notion of cyclic pursuit by examining a system of identical linear agents in the plane. This idea is then extended to a system of wheeled ..."
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Cited by 118 (2 self)
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Inspired by the socalled “bugs” problem from mathematics, we study the geometric formations of multivehicle systems under cyclic pursuit. First, we introduce the notion of cyclic pursuit by examining a system of identical linear agents in the plane. This idea is then extended to a system of wheeled vehicles, each subject to a single nonholonomic constraint (i.e., unicycles), which is the principal focus of this paper. The pursuit framework is particularly simple in that the identical vehicles are ordered such that vehicle pursues vehicle CImodulo. In this paper, we assume each vehicle has the same constant forward speed. We show that the system’s equilibrium formations are generalized regular polygons and it is exposed how the multivehicle system’s global behavior can be shaped through appropriate controller gain assignments. We then study the local stability of these equilibrium polygons, revealing which formations are stable and which are not.
Controlling individual agents in highdensity crowd simulation
 Proc. of ACM SIGGRAPH / Eurographics Symposium on Computer Animation (SCA
, 2007
"... Simulating the motion of realistic, large, dense crowds of autonomous agents is still a challenge for the computer graphics community. Typical approaches either resemble particle simulations (where agents lack orientation controls) or are conservative in the range of human motion possible (agents la ..."
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Cited by 111 (10 self)
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Simulating the motion of realistic, large, dense crowds of autonomous agents is still a challenge for the computer graphics community. Typical approaches either resemble particle simulations (where agents lack orientation controls) or are conservative in the range of human motion possible (agents lack psychological state and aren’t allowed to ‘push ’ each other). Our HiDAC system (for HighDensity Autonomous Crowds) focuses on the problem of simulating the local motion and global wayfinding behaviors of crowds moving in a natural manner within dynamically changing virtual environments. By applying a combination of psychological and geometrical rules with a social and physical forces model, HiDAC exhibits a wide variety of emergent behaviors from agent line formation to pushing behavior and its consequences; relative to the current situation, personalities of the individuals and perceived social density.
PingPongPlus: Design of an AthleticTangible Interface for ComputerSupported Cooperative Play
, 1999
"... This paper introduces a novel interface for digitallyaugmented cooperative play. We present the concept of the "athletictangible interface," a new class of interaction which uses tangible objects and fullbody motion in physical spaces with digital augmentation. We detail the implementati ..."
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Cited by 108 (8 self)
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This paper introduces a novel interface for digitallyaugmented cooperative play. We present the concept of the "athletictangible interface," a new class of interaction which uses tangible objects and fullbody motion in physical spaces with digital augmentation. We detail the implementation of PingPongPlus, a "reactive pingpong table", which features a novel soundbased ball tracking technology. The game is augmented and transformed with dynamic graphics and sound, determined by the position of impact, and the rhythm and style of play. A variety of different modes of play and initial experiences with PingPongPlus are also described. Keywords tangible interface, enhanced reality, augmented reality, interactive surface, athletic interaction, kinesthetic interaction, computersupported cooperative play. INTRODUCTION When an expert plays pingpong, a wellused paddle becomes transparent, and allows a player to concentrate on the task  playing pingpong. The good fit of grasp is vit...
Distributed, PhysicsBased Control of Swarms of Vehicles
 Autonomous Robots
"... We introduce a framework, called "physicomimetics," that provides distributed control of large collections of mobile physical agents in sensor networks. The agents sense and react to virtual forces, which are motivated by natural physics laws. Thus, physicomimetics is founded upon solid sc ..."
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Cited by 105 (25 self)
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We introduce a framework, called "physicomimetics," that provides distributed control of large collections of mobile physical agents in sensor networks. The agents sense and react to virtual forces, which are motivated by natural physics laws. Thus, physicomimetics is founded upon solid scientific principles. Furthermore, this framework provides an effective basis for selforganization, faulttolerance, and selfrepair. Three primary factors distinguish our framework from others that are related: an emphasis on minimality (e.g., cost effectiveness of large numbers of agents implies a need for expendable platforms with few sensors), ease of implementation, and runtime efficiency. Examples are shown of how this framework has been applied to construct various regular geometric lattice configurations (distributed sensing grids), as well as dynamic behavior for perimeter defense and surveillance. Analyses are provided that facilitate system understanding and predictability, including both qualitative and quantitative analyses of potential energy and a system phase transition. Physicomimetics has been implemented both in simulation and on a team of seven mobile robots. Specifics of the robotic embodiment are presented in the paper.
Spatiallydistributed coverage optimization and control with limitedrange interactions
 ESAIM Control, Optimisation Calculus Variations
, 2005
"... Abstract. This paper presents coordination algorithms for groups of mobile agents performing deployment and coverage tasks. As an important modeling constraint, we assume that each mobile agent has a limited sensing/communication radius. Based on the geometry of Voronoi partitions and proximity grap ..."
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Cited by 95 (30 self)
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Abstract. This paper presents coordination algorithms for groups of mobile agents performing deployment and coverage tasks. As an important modeling constraint, we assume that each mobile agent has a limited sensing/communication radius. Based on the geometry of Voronoi partitions and proximity graphs, we analyze a class of aggregate objective functions and propose coverage algorithms in continuous and discrete time. These algorithms have convergence guarantees and are spatially distributed with respect to appropriate proximity graphs. Numerical simulations illustrate the results.
Globular Dynamics: A Connected Particle System For Animating Viscous Fluids
, 1989
"... Connected particle systems can depict many objects difficult to model in any other fashion. We present a method for animating viscous fluids by simulating the forces of such particles interacting with each other. This method allows for collision detection between the particles and obstacles, both ..."
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Cited by 90 (1 self)
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Connected particle systems can depict many objects difficult to model in any other fashion. We present a method for animating viscous fluids by simulating the forces of such particles interacting with each other. This method allows for collision detection between the particles and obstacles, both stationary and mobile, and it allows solid objects to break and melt. An approximate method for covering the particles with an isosurface for efficient rendering is also presented.