Motion Coordination with Distributed Information

Motion coordination is a remarkable phenomenon in biological systems and an extremely useful tool for groups of vehicles, mobile sensors, and embedded robotic systems. For many applications, teams of mobile autonomous agents need the ability to deploy over a region, assume a specified pattern, rendezvous at a common point, or move in a synchronized manner. The objective of this article is to illustrate the use of systems theory to analyze emergent behaviors in animal groups and to design autonomous and reliable robotic networks. We present and survey some recently developed theoretical tools for modeling, analysis, and design of motion coordination algorithms in both continuous and discrete time. We pay special attention to the distributed character of coordination algorithms, the characterization of their performance, and the development of design methodologies that provide mobile networks with provably correct cooperative strategies.

[1]  George J. Pappas,et al.  Flocking in Fixed and Switching Networks , 2007, IEEE Transactions on Automatic Control.

[2]  S. Yau.  Mathematics and its applications , 2002 .

[3]  Sonia Martínez,et al.  Coverage control for mobile sensing networks , 2002, IEEE Transactions on Robotics and Automation.

[4]  Brian D. O. Anderson,et al.  The Multi-Agent Rendezvous Problem. An Extended Summary , 2005 .

[5]  Wei Ren,et al.  Information consensus in multivehicle cooperative control , 2007, IEEE Control Systems.

[6]  A. Bacciotti,et al.  Stability and Stabilization of Discontinuous Systems and Nonsmooth Lyapunov Functions , 1999 .

[7]  George J. Pappas,et al.  Stability of Flocking Motion , 2003 .

[8]  Reza Olfati-Saber,et al.  Flocking for multi-agent dynamic systems: algorithms and theory , 2006, IEEE Transactions on Automatic Control.

[9]  Aleksej F. Filippov,et al.  Differential Equations with Discontinuous Righthand Sides , 1988, Mathematics and Its Applications.

[10]  P. S. Krishnaprasad,et al.  Equilibria and steering laws for planar formations , 2004, Syst. Control. Lett..

[11]  Sonia Martínez,et al.  Robust rendezvous for mobile autonomous agents via proximity graphs in arbitrary dimensions , 2006, IEEE Transactions on Automatic Control.

[12]  David G. Luenberger,et al.  Linear and nonlinear programming , 1984 .

[13]  F. Bullo,et al.  On Synchronous Robotic Networks—Part I: Models, Tasks, and Complexity , 2005, IEEE Transactions on Automatic Control.

[14]  Mehran Mesbahi,et al.  On state-dependent dynamic graphs and their controllability properties , 2004, 2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601).

[15]  Frank Harary,et al.  Graph Theory , 2016 .

[16]  Vicsek,et al.  Novel type of phase transition in a system of self-driven particles. , 1995, Physical review letters.

[17]  Vladimir J. Lumelsky,et al.  Decentralized Motion Planning for Multiple Mobile Robots: The Cocktail Party Model , 1997, Auton. Robots.

[18]  Jie Lin,et al.  Coordination of groups of mobile autonomous agents using nearest neighbor rules , 2003, IEEE Trans. Autom. Control..

[19]  Kevin M. Passino,et al.  Stability analysis of swarms , 2003, IEEE Trans. Autom. Control..

[20]  Steven V. Viscido,et al.  Self-Organized Fish Schools: An Examination of Emergent Properties , 2002, The Biological Bulletin.

[21]  Mark de Berg,et al.  Computational geometry: algorithms and applications , 1997 .

[22]  Calin Belta,et al.  Abstraction and control for Groups of robots , 2004, IEEE Transactions on Robotics.

[23]  S. Gueron,et al.  Self-organization of front patterns in large wildebeest herds , 1993 .

[24]  Vikrant Sharma,et al.  Time Complexity of Sensor-Based Vehicle Routing , 2005, Robotics: Science and Systems.

[25]  Mireille E. Broucke,et al.  Formations of vehicles in cyclic pursuit , 2004, IEEE Transactions on Automatic Control.

[26]  Emilio Frazzoli,et al.  On synchronous robotic networks Part I: Models, tasks and complexity notions , 2007, Proceedings of the 44th IEEE Conference on Decision and Control.

[27]  Masafumi Yamashita,et al.  Distributed memoryless point convergence algorithm for mobile robots with limited visibility , 1999, IEEE Trans. Robotics Autom..

[28]  J. E. Harding,et al.  Engineering mechanics—statics and an introduction to dynamics (2nd edition) , 1989 .

[29]  Francesco Bullo,et al.  Coordination and Geometric Optimization via Distributed Dynamical Systems , 2003, SIAM J. Control. Optim..

[30]  Aimee F. Campbell,et al.  Use of Trill Vocalizations To Coordinate Troop Movement Among White-Faced Capuchins: a Second Field Test , 1995 .

[31]  Atsuyuki Okabe,et al.  Spatial Tessellations: Concepts and Applications of Voronoi Diagrams , 1992, Wiley Series in Probability and Mathematical Statistics.

[32]  Qiang Du,et al.  Centroidal Voronoi Tessellations: Applications and Algorithms , 1999, SIAM Rev..

[33]  Seif Haridi,et al.  Distributed Algorithms , 1992, Lecture Notes in Computer Science.

[34]  Franz Aurenhammer,et al.  Voronoi diagrams—a survey of a fundamental geometric data structure , 1991, CSUR.

[35]  Masafumi Yamashita,et al.  Distributed Anonymous Mobile Robots: Formation of Geometric Patterns , 1999, SIAM J. Comput..

[36]  Carl D. Meyer,et al.  Matrix Analysis and Applied Linear Algebra , 2000 .

[37]  Petter Ögren,et al.  Cooperative control of mobile sensor networks:Adaptive gradient climbing in a distributed environment , 2004, IEEE Transactions on Automatic Control.

[38]  Mireille E. Broucke,et al.  Local control strategies for groups of mobile autonomous agents , 2004, IEEE Transactions on Automatic Control.

[39]  Eric Klavins,et al.  A grammatical approach to self-organizing robotic systems , 2006, IEEE Transactions on Automatic Control.

[40]  A. Harcourt,et al.  Gorillas' Vocalizations During Rest Periods: Signals of Impending Departure? , 1994 .

[41]  Emilio Frazzoli,et al.  Synchronous robotic networks and complexity of control and communication laws , 2005 .

[42]  A. Ōkubo.  Dynamical aspects of animal grouping: swarms, schools, flocks, and herds. , 1986, Advances in biophysics.

[43]  Richard M. Murray,et al.  Consensus problems in networks of agents with switching topology and time-delays , 2004, IEEE Transactions on Automatic Control.

[44]  Lynne E. Parker,et al.  Robot Teams: From Diversity to Polymorphism , 2002 .

[45]  Alfred M. Bruckstein,et al.  Ants, Crickets and Frogs in Cyclic Pursuit , 1991 .

[46]  Randal W. Beard,et al.  Consensus seeking in multiagent systems under dynamically changing interaction topologies , 2005, IEEE Transactions on Automatic Control.

[47]  T. Seeley,et al.  Group decision making in swarms of honey bees , 1999, Behavioral Ecology and Sociobiology.

[48]  Gaurav S. Sukhatme,et al.  Mobile Sensor Network Deployment using Potential Fields : A Distributed , Scalable Solution to the Area Coverage Problem , 2002 .

[49]  F. Bullo,et al.  Decentralized algorithms for vehicle routing in a stochastic time-varying environment , 2004, 2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601).

[50]  Elias Levy,et al.  Worst-Case Scenario , 2006, IEEE Security & Privacy.

[51]  A. Sinclair,et al.  The African Buffalo: A Study of Resource Limitation of Populations , 1978 .

[52]  Ronald C. Arkin,et al.  An Behavior-based Robotics , 1998 .

[53]  John N. Tsitsiklis,et al.  Parallel and distributed computation , 1989 .

[54]  Luc Moreau,et al.  Stability of multiagent systems with time-dependent communication links , 2005, IEEE Transactions on Automatic Control.

[55]  Godfried T. Toussaint,et al.  Relative neighborhood graphs and their relatives , 1992, Proc. IEEE.

[56]  B. Bassler,et al.  Quorum sensing in bacteria. , 2001, Annual review of microbiology.

[57]  Francesco Bullo,et al.  Esaim: Control, Optimisation and Calculus of Variations Spatially-distributed Coverage Optimization and Control with Limited-range Interactions , 2022 .

[58]  I. Couzin,et al.  Effective leadership and decision-making in animal groups on the move , 2005, Nature.

[59]  T. J. Roper,et al.  Group decision-making in animals , 2003, Nature.