This paper describes decentralized control laws for the coordination of multiple vehicles performing spatially distributed tasks. The control laws are based on a gradient descent scheme applied to a class of decentralized utility functions that encode optimal coverage and sensing policies. These utility functions are studied in geographical optimization problems and they arise naturally in vector quantization and in sensor allocation tasks. The approach exploits the computational geometry of spatial structures such as Voronoi diagrams.

/pdf/coverage-control-for-mobile-sensing-networks-3gs75qafnm.pdf

Coverage control for mobile sensing networks

This paper presents control and coordination algorithms for groups of vehicles. The focus is on autonomous vehicle networks performing distributed sensing tasks where each vehicle plays the role of a mobile tunable sensor. The paper proposes gradient descent algorithms for a class of utility functions which encode optimal coverage and sensing policies. The resulting closed-loop behavior is adaptive, distributed, asynchronous, and verifiably correct.

Despite more than a decade of experimental work in multi-robot systems, important theoretical aspects of multi-robot coordination mechanisms have, to date, been largely untreated. To address this issue, we focus on the problem of multi-robot task allocation (MRTA). Most work on MRTA has been ad hoc and empirical, with many coordination architectures having been proposed and validated in a proof-of-concept fashion, but infrequently analyzed. With the goal of bringing objective grounding to this important area of research, we present a formal study of MRTA problems. A domain-independent taxonomy of MRTA problems is given, and it is shown how many such problems can be viewed as instances of other, well-studied, optimization problems. We demonstrate how relevant theory from operations research and combinatorial optimization can be used for analysis and greater understanding of existing approaches to task allocation, and show how the same theory can be used in the synthesis of new approaches.

/pdf/a-formal-analysis-and-taxonomy-of-task-allocation-in-multi-37udlnz144.pdf

A Formal Analysis and Taxonomy of Task Allocation in Multi-Robot Systems

This self-contained introduction to the distributed control of robotic networks offers a distinctive blend of computer science and control theory. The book presents a broad set of tools for understanding coordination algorithms, determining their correctness, and assessing their complexity; and it analyzes various cooperative strategies for tasks such as consensus, rendezvous, connectivity maintenance, deployment, and boundary estimation. The unifying theme is a formal model for robotic networks that explicitly incorporates their communication, sensing, control, and processing capabilities--a model that in turn leads to a common formal language to describe and analyze coordination algorithms.Written for first- and second-year graduate students in control and robotics, the book will also be useful to researchers in control theory, robotics, distributed algorithms, and automata theory. The book provides explanations of the basic concepts and main results, as well as numerous examples and exercises.Self-contained exposition of graph-theoretic concepts, distributed algorithms, and complexity measures for processor networks with fixed interconnection topology and for robotic networks with position-dependent interconnection topology Detailed treatment of averaging and consensus algorithms interpreted as linear iterations on synchronous networks Introduction of geometric notions such as partitions, proximity graphs, and multicenter functions Detailed treatment of motion coordination algorithms for deployment, rendezvous, connectivity maintenance, and boundary estimation

/pdf/distributed-control-of-robotic-networks-a-mathematical-1q6nfcvi2l.pdf

Distributed Control of Robotic Networks: A Mathematical Approach to Motion Coordination Algorithms

Market-based multirobot coordination approaches have received significant attention and are growing in popularity within the robotics research community. They have been successfully implemented in a variety of domains ranging from mapping and exploration to robot soccer. The research literature on market-based approaches to coordination has now reached a critical mass that warrants a survey and analysis. This paper addresses this need for a survey of the relevant literature by providing an introduction to market-based multirobot coordination, a review and analysis of the state of the art in the field, and a discussion of remaining research challenges

/pdf/market-based-multirobot-coordination-a-survey-and-analysis-54mewq3cve.pdf

Market-Based Multirobot Coordination: A Survey and Analysis

Preface. Part I: Planning and Task Allocation. On Architectural and Decisional Issues for Multi-Robot Cooperation R. Alami. A Framework for Studying Multi-Robot Task Allocation B.P. Gerkey, M.J. Matarie. Market-Based Multi-Robot Planning in a Distributed Layered Architecture D. Goldberg, V. Cicirello, M.B. Dias Reid Simmons, S. Smith, A. Stentz. Collaborative Tasking of Tightly Constrained Multi-Robot Missions D.C. MacKenzie. Part II: Coordination and Control. Multi-Objective Navigation and Control Using Interval Prograniming M.R. Benjamin. Cooperative Relative Localization for Mobile Robot Teams: An Ego-Centric Approach A. Howard, M.J. Mataric, G.S. Sukhatine. Fractional Bandwidth Reacquisition Algorithms for VSW-MCM B. Cook, D. Marthaler, C. Topaz, A. Bertozzi, M. Kemp. Dynamic Multi-Robot Coordination D. Vail, M. Veloso. Part III: Sensor and Information Fusion. Information Sharing in Teams of Self-Aware Entities J. Franke, B. Satterfield, S. Jameson. Realizing Virtual Sensors by Distributed Multi-Level Sensor Fusion E. Nett, S. Schemmer. Information Fusion and Control for Multiple UAVs S. Sukkarieh, E. Nettleton, B. Grocholsky, H. Durrant-Whyte. Part IV: Learning. Multistrategy Learning Methods for Multirobot Systems R.C. Arkin, Y. Endo, B. Lee, D. MacKenzie, E. Martinson. Part V: Self-Reconfigurable Robots. Distributed Locomotion Algorithms for Self-Reconfigurable Robots Operating on Rough Terrain Z. Butler, D. Rus. Self-Assembly in Space via Self-Reconfigurable Robots Wei-Min Shen, P. Will, B. Khoshnevis. Part VI: Large-Scale Robot Teams. Optimization of Swarm Robotic Systems via Macroscopic Models A. Martinoli, K. Easton. CentiBOTS: Large Scale Robot Teams K. Konolige, C. Ortiz, R. Vincent, A. Agno, M. Eriksen, B. Limketkai, M. Lewis, L. Briesemeister, E. Ruspini, D. Fox, J. Ko, B. Stewart, L. Guibas. The Effect of Heterogeneity in Teams of 100+ Mobile Robots L.E. Parker. Part VII: Human-Robot Teams. Collaborative Tools for Mixed Teams of Humans and Robots D.J. Bruemmer, M.C. Walton. Mixed-Initiative Control of Large Human-Robot Teams C.L. Johnson. Experiments in Human-Robot Teams C.W. Nielsen, M.A. Goodrich, J.W. Crandall. Impact of Autonomy in Multirobot Systems on Teleoperation Performance B. Trouvain, H.L. Wolf, F.E. Schneider. Part VIII: Communication Constraint and Networks. Decentralized Motion Planning for Multiple Robots Subject to Sensing and Communication Constraints G.A.S. Pereira, A.K. Das, V. Kumar, M.F.M. Campos. Exploiting the Interactions Between Robotic Autonomy and Networks J. Redi, J. Bers. Part IX: Poster Abstracts. Observing Multiple Targets with Multiple Mobile Robots Using Probabilistic Behavior-Based Techniques T. Balch, A. Stroupe. Dynamic Coverage via Multi-robot Cooperation M.A. Batalin, G.S. Sukhatme. Emergent Control Surveillance Networks R.R. Brooks, J. Lamb, M. Pirretti, M. Zhu, S.S. Iyengar. On Dynamic Reconfiguration of Multi-Robot Formations R. Fierro, A.K. Das. Distributed Multi-Robot Mapping D. Fox, J. Ko, B. Stewart, K. Konolige, B. Limetkai. An Endogeneous Architecture for Cooperative Sensor Teams B. Grocholsky, A. Makarenko, H. Durrant-Whyte. Efficient Inference Grounding for Distributed Multi-Robot Teams A. Khoo, I.D. Horswill. Author Index.

Multi-Robot Systems: From Swarms to Intelligent Automata

We address the basic problem of coordinating the actions of multiple robots that are working toward a common goal. This kind of problem is NP-hard, because in order to coordinate a system of n robots, it is in principle necessary to generate and evaluate a number of actions or plans that is exponential in n (assuming P 6= NP ). However, we suggest that many instances of coordination problems, despite the NP-hardness of the overall class of problems, do not in practice require exponential computation in order to arrive at good solutions. In such problems, it is not necessary to consider all possible actions of the n robots; instead an algorithm may restrict its attention to interactions within small teams, and still produce high-quality solutions. We use this insight in the development of a novel coordination algorithm that we call parallel stochastic hill-climbing with small teams, or Parish. This algorithm is designed specifically for use in multi-robot systems: it can run off-line or on-line, is easily distributed across multiple machines, and is efficient with regard to communication. We state and analyze the Parish algorithm present results from the implementation and application of the algorithm for a concrete problem: multi-robot pursuit-evasion. In this demanding domain, a team of robots must coordinate their actions so as to guarantee location of a skilled evader.

http://www.ai.sri.com/~gerkey/papers/small-teams.pdf

Multi-Robot Systems. From Swarms to Intelligent Automata Volume III

Multi-robot systems : from swarms to intelligent automata : proceedings from the 2003 International Workshop on Multi-Robot Systems

Preface. Part I Task Allocation. The Generation of Bidding Rules for Auction-Based Robot Coordination. Craig Tovey, Michail G. Lagoudakis, Sonal fain, Sven Koenig. Issues in Multi-Robot Coalition Formation. Lovekesh Vig, Julie A. Adams. Sensor Network-Mediated Multi-Robot Task Allocation. Maxim A. Batalin and Gaurav S. Sukhatme. Part II Coordination in Dynamic Environments. Multi-Objective Cooperative Control of Dynamical Systems. Zhihua Qu, fing Wang, Richard A. Hull. Levels of Multi-Robot Coordination for Dynamic Environments. Cohn P. McMillen, Paul E. Rybski, Manuela M. Veloso. Parallel Stochastic Hill-Climbing with Small Teams. Brian P. Gerkey, Sebastian Thrun, Geoff Gordon. Toward Versatility of Multi-Robot Systems. Cohn Cherry and Hong Zhang. Part III Information/ Sensor Sharing and Fusion. Decentralized Communication Strategies. Maayan Roth, Reid Simmons, and Manuela Veloso. Improving Multirobot Multitarget Tracking. Matthew Powers, Ramp rasad Ravichandran, Frank Dehlaert, Tucker Baich. Enabling Autonomous Sensor-Sharing. Lynne E. Parker, Maureen Chandra, Fang Tang. Part IV Distributed Mapping and Coverage. Merging Partial Maps without Using Odometry. Francesco Amigoni, Simone Gasparini, Maria Gini. Distributed Coverage of Unknown/Unstructured Environments by Mobile Sensor Networks. Ioannis Rekleitis, Ai Peng New, Howie Choset. Part V Motion Planning and Control. Motion Planning with Safe Dynamics. James Bruce and Manuela Veloso. A Multi-Robot Testbed for Biologically-Inspired Cooperative Control. Rafael Fierro and Justin Clark, Dean Hougen and Sesh Commuri. Part VI Human-Robot Interaction. Task Switching and Multi-Robot Teams. Michael A. Goodrich, Morgan Quigley, Keryl Cosenzo. User Modeling for Principled Sliding Autonomy in Human-Robot Teams. Brennan Seilner, Reid Simmons, Sanjiv Singh. Part VII Applications. Multi-Robot Chemical Plume Tracing. Diana Spears, Dimitri Zarzhitsky, David Thayer. Deploying Air-Ground Multi-Robot Teamsin Urban Environments. L. Chaimowicz, A. Cowley, D. Gomez-Ibanez, B. Grochoisky, M.A. Hsieh, H. Hsu, J.F. Keller, V Kumar, R. Swaminathan, C.J. Taylor. Precision Manipulation with Cooperative Robots. Ashley Stroupe, Terry Huntsberger, Avi Okon, Hrand Aghazarian. Part VIII Poster Short Papers. A Robust Monte-Carlo Algorithm for Multi-Robot Localization. Vazha Amiranashvili, Gerhard Lakemeyer. A Dialogue-Based Approach to Multi-Robot Team Control. Nathanael Chambers, James Allen, Lucian Galescu, Hyuckchul Jung. Hybrid FSO/RF Networks for Mobile Robot Teams. Jason Derenick, Christopher Thorne, and John Spletzer. Swarming UAVS Behavior Hierarchy. Kuo-Chi Lin. The GNATs. Keith J. O'Hara, Daniel B. Walker, and Tucker R. Balch. Role Based Operations. Brian Satterfield, Heeten Choxi, and Drew Housten. Ergodic Dynamics by Design. Dylan A. Shell, Chris V. Jones, Maja J. Matarie.

Multi-robot systems : from swarms to intelligent automata volume III : proceedings from the 2005 International Workshop on Multi-Robot Systems

Preface. Part I: Localization, Mapping and Navigation. On the Positional Uncertainty of Multi-Robot Cooperative Localization I.M. Rekleitis, et al. A Multi-Agent System for Multi-Robot Mapping and Exploration K. Konolige, et al. Distributed Heterogeneous Sensing for Outdoor Multi-Robot Localization, Mapping, and Path Planning L.E. Parker. et al. Mission-Relevant Collaborative Observation and Localization A.W. Stroupe, T. Balch. Deployment and Localization for Mobile Robot Teams A. Howard, M.J. Mataric. Multiple Autonomous Robots for UXO Clearance, the Basic UXO Gathering System (BUGS) Project T.N. Nguyen, et al. Part II: Distributed Survelliance. Programming and Controlling the Operations of a Team of Miniature Robots P.E. Rybski, et al. Autonomous Flying Vehicle Research at the University of Southern California S. Saripalli, et al. Part III: Manipulation. Distributed Manipulation of Multiple Objects Using Ropes B. Donald, et al. A Distributed Multi-Robot System for Cooperative Manipulation A. Das, et al. Part IV: Coordination and Formations. A Layered Architecture for Coordination of Mobile Robots R. Simmons, et al. Stability Analysis of Decentralized Cooperative Controls J.T. Feddema, D.A. Schoenwald. Snow White and the 700 Dwarves B.H. Wilcox. Part V: Sensor and Hardware Issues. GOATS: Multi-platform Sonar Concept for Coastal Mine Countermeasures H. Schmidt, J.R. Edwards. Design of the UMN Multi-Robot System A. Drenner, et al. Simulating Self-Organization With the Digital Hormone Model Wei-Min Shen, Cheng-Ming Chuong. Part VI: Design and Learning. Architecting a Simulation and Development Environment for Multi-Robot Teams S. Balakirsky, et al. RobotSoccer: A Multi-Robot Challenge M.M. Veloso. Part VII: Human/Robot Interaction. Human-Robot Interactions: Creating Synergistic Cyber Forces J.C. Scholtz. Communicating with Teams of Cooperative Robots D. Perzanowski, et al. Robot as Partner: Vehicle Tele-operation with Collaborative Control T. Fong, et al. Adaptive Multi-Robot, Multi-Operator Work Systems A.C. Morris, et al. User Interaction with Multi-Robot Systems D. Kortenkamp, et al. Human-Robot Interactions in Robot-Assisted Urban Search and Rescue R. Murphy, J. Casper. Usability Issues for Designing Multi-Robot Missions R.C. Arkin. Perception-Based Navigation for Mobile Robots K. Kawamura, et al. Author Index.

Multi-Robot systems: from swarms to intelligent automata : proceedings from the 2002 NRL workshop on multi-robot systems

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