Scalable Control of Distributed Robotic Macrosensors

This paper describes a control mechanism by which large numbers of inexpensive robots can be deployed as a distributed remote sensing instrument, and in which the desired large-scale properties of the sensing instrument emerge from the simple pair-wise interactions of its component robots. Such sensing instruments are called distributed robotic macrosensors. Robots in the macrosensor interact with their immediate neighbors using a virtual spring mesh abstraction, which is governed by a simple physics model. By carefully defining the nature of the spring mesh and the associated physics model, it is possible to create a number of desirable global behaviors without any global control or configuration. Properties of the resulting macrosensor include arbitrary scalability, the ability to function in complex environments, sophisticated target tracking ability, and natural fault tolerance. We describe the control mechanisms that yield these results, and the simulation results that demonstrate their efficacy.

[1]  R. Sokal,et al.  A New Statistical Approach to Geographic Variation Analysis , 1969 .

[2]  D. Matula,et al.  Properties of Gabriel Graphs Relevant to Geographic Variation Research and the Clustering of Points in the Plane , 2010 .

[3]  Steven Fortune,et al.  A sweepline algorithm for Voronoi diagrams , 1986, SCG '86.

[4]  M. Merriam An Entropy-Based Approach to Nonlinear Stability , 1989 .

[5]  Rodney A. Brooks,et al.  Integrated systems based on behaviors , 1991, SGAR.

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

[7]  Douglas W. Gage,et al.  Command Control for Many-Robot Systems , 1992 .

[8]  B. Argrow,et al.  Entropy production in finite-difference schemes , 1993 .

[9]  Lynne E. Parker,et al.  ALLIANCE: an architecture for fault tolerant, cooperative control of heterogeneous mobile robots , 1994 .

[10]  Douglas W. Gage,et al.  Randomized search strategies with imperfect sensors , 1994, Other Conferences.

[11]  Tucker R. Balch,et al.  Motor Schema-Based Formation Control for Multiagent Robot Teams , 1995, ICMAS.

[12]  Lynne E. Parker,et al.  On the design of behavior-based multi-robot teams , 1995, Adv. Robotics.

[13]  Christian Laugier,et al.  Adaptive time step for fast converging dynamic simulation system , 1996, Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems. IROS '96.

[14]  Lynne E. Parker,et al.  Cooperative multi-robot observation of multiple moving targets , 1997, Proceedings of International Conference on Robotics and Automation.

[15]  Josep Amat,et al.  Map Generation by Cooperative Low-Cost Robots in Structured Unknown Environments , 1998, Auton. Robots.

[16]  Tucker R. Balch,et al.  Behavior-based formation control for multirobot teams , 1998, IEEE Trans. Robotics Autom..

[17]  Brian Shucker,et al.  Geometric Attitude Control of a Small Satellite for Ground Tracking Maneuvers , 1999 .

[18]  Insup Lee,et al.  Distributed Spatial Control, Global Monitoring and Steering of Mobile Physical Agents , 1999 .

[19]  William M. Spears,et al.  Using artificial physics to control agents , 1999, Proceedings 1999 International Conference on Information Intelligence and Systems (Cat. No.PR00446).

[20]  Insup Lee,et al.  Distributed spatial control, global monitoring and steering of mobile agents , 1999, Proceedings 1999 International Conference on Information Intelligence and Systems (Cat. No.PR00446).

[21]  Hiroaki Yamaguchi,et al.  A Cooperative Hunting Behavior by Mobile-Robot Troops , 1999, Int. J. Robotics Res..

[22]  Barry Brian Werger,et al.  Cooperation without Deliberation: A Minimal Behavior-based Approach to Multi-Robot Teams , 1999, Artif. Intell..

[23]  A. Morse,et al.  Stability of switched systems with average dwell-time , 1999, Proceedings of the 38th IEEE Conference on Decision and Control (Cat. No.99CH36304).

[24]  Hari Balakrishnan,et al.  6th ACM/IEEE International Conference on on Mobile Computing and Networking (ACM MOBICOM ’00) The Cricket Location-Support System , 2022 .

[25]  Kurt Konolige,et al.  A gradient method for realtime robot control , 2000, Proceedings. 2000 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2000) (Cat. No.00CH37113).

[26]  Tucker R. Balch,et al.  Behavior-based coordination of large-scale robot formations , 2000, Proceedings Fourth International Conference on MultiAgent Systems.

[27]  Wolfram Burgard,et al.  Coordination for Multi-Robot Exploration and Mapping , 2000, AAAI/IAAI.

[28]  Wolfram Burgard,et al.  A real-time algorithm for mobile robot mapping with applications to multi-robot and 3D mapping , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[29]  J. Hespanha Extending LaSalle's invariance principle to switched linear systems , 2001, Proceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228).

[30]  Thomas S. Brinsmead,et al.  Multiple model adaptive control. Part 2: switching , 2001 .

[31]  Maja J. Matarić,et al.  Cover Me! A Self-Deployment Algorithm for Mobile Sensor Networks , 2001 .

[32]  Mario Gerla,et al.  Fault Tolerance and Load Balancing in QoS Provisioning with Multiple MPLS Paths , 2001, IWQoS.

[33]  Xiaoyan Hong,et al.  The Mars sensor network: efficient, energy aware communications , 2001, 2001 MILCOM Proceedings Communications for Network-Centric Operations: Creating the Information Force (Cat. No.01CH37277).

[34]  Gaurav S. Sukhatme,et al.  Most valuable player: a robot device server for distributed control , 2001, Proceedings 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems. Expanding the Societal Role of Robotics in the the Next Millennium (Cat. No.01CH37180).

[35]  Sven Koenig,et al.  Terrain coverage with ant robots: a simulation study , 2001, AGENTS '01.

[36]  Brian Shucker,et al.  A Ground-Based Prototype of a CMOS Navigational Star Camera for Small Satellite Applications , 2001 .

[37]  Gaurav S. Sukhatme,et al.  Tracking Targets Using Multiple Robots: The Effect of Environment Occlusion , 2002, Auton. Robots.

[38]  Wei Hong,et al.  Proceedings of the 5th Symposium on Operating Systems Design and Implementation Tag: a Tiny Aggregation Service for Ad-hoc Sensor Networks , 2022 .

[39]  Magnus Egerstedt On the Specification Complexity of Linguistic Control Procedures , 2002 .

[40]  David E. Culler,et al.  Supporting aggregate queries over ad-hoc wireless sensor networks , 2002, Proceedings Fourth IEEE Workshop on Mobile Computing Systems and Applications.

[41]  Xiaoyan Hong,et al.  Load balanced, energy-aware communications for Mars sensor networks , 2002, Proceedings, IEEE Aerospace Conference.

[42]  Kevin A. Delin The Sensor Web: A Macro-Instrument for Coordinated Sensing , 2002 .

[43]  Erol Sahin,et al.  Measurement of Space: From Ants to Robots , 2002 .

[44]  Katia Sycara,et al.  Team-Oriented Agent Coordination in the RETSINA Multi-Agent System , 2002 .

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

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

[47]  Richard Han,et al.  VLM2: A Very Lightweight Mobile Multicast System for Wireless Sensor Networks ; CU-CS-938-02 , 2002 .

[48]  Naomi Ehrich Leonard,et al.  Vehicle networks for gradient descent in a sampled environment , 2002, Proceedings of the 41st IEEE Conference on Decision and Control, 2002..

[49]  Manuela Veloso,et al.  A World Model for Multi-Robot Teams with Communication , 2002 .

[50]  William M. Spears,et al.  Analysis of a Phase Transition in a Physics-Based Multiagent System , 2002, FAABS.

[51]  George J. Pappas,et al.  Stable flocking of mobile agents, part I: fixed topology , 2003, 42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475).

[52]  Daniel Liberzon,et al.  Switching in Systems and Control , 2003, Systems & Control: Foundations & Applications.

[53]  Dale Lawrence,et al.  Lyapunov Vector Fields for UAV Flock Coordination , 2003 .

[54]  Jeff Rose,et al.  MANTIS: system support for multimodAl NeTworks of in-situ sensors , 2003, WSNA '03.

[55]  Jun Ota,et al.  Cooperative exploration of mobile robots using reaction-diffusion equation on a graph , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[56]  George J. Pappas,et al.  Stable flocking of mobile agents part I: dynamic topology , 2003, 42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475).

[57]  Gaurav S. Sukhatme,et al.  Sensor network-based multi-robot task allocation , 2003, Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453).

[58]  Stefano Nolfi,et al.  Evolving Mobile Robots Able to Display Collective Behaviors , 2003, Artificial Life.

[59]  Shivakant Mishra,et al.  A Performance Evaluation of Intrusion-Tolerant Routing in Wireless Sensor Networks , 2003, IPSN.

[60]  R. Murray,et al.  Consensus protocols for networks of dynamic agents , 2003, Proceedings of the 2003 American Control Conference, 2003..

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

[62]  Kristofer S. J. Pister,et al.  CotsBots: an off-the-shelf platform for distributed robotics , 2003, Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453).

[63]  Shivakant Mishra,et al.  Intrusion tolerance and anti-traffic analysis strategies for wireless sensor networks , 2004, International Conference on Dependable Systems and Networks, 2004.

[64]  Prithwish Basu,et al.  Movement control algorithms for realization of fault-tolerant ad hoc robot networks , 2004, IEEE Network.

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

[66]  James McLurkin,et al.  Distributed Algorithms for Dispersion in Indoor Environments Using a Swarm of Autonomous Mobile Robots , 2004, DARS.

[67]  Maja J. Mataric,et al.  From insect to Internet: Situated control for networked robot teams , 2001, Annals of Mathematics and Artificial Intelligence.

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

[69]  David E. Culler,et al.  The dynamic behavior of a data dissemination protocol for network programming at scale , 2004, SenSys '04.

[70]  Timothy X. Brown,et al.  Ad Hoc UAV Ground Network (AUGNet) , 2004 .

[71]  Maria Gini,et al.  Dispersing robots in an unknown environment , 2004, DARS.

[72]  B. Shucker,et al.  Target tracking with distributed robotic macrosensors , 2005, MILCOM 2005 - 2005 IEEE Military Communications Conference.

[73]  John K. Bennett,et al.  Virtual Spring Mesh Algorithms for Control of Distributed Robotic Macrosensors ; CU-CS-996-05 , 2005 .

[74]  Peng Yang,et al.  Distributed estimation and control of swarm formation statistics , 2006, 2006 American Control Conference.

[75]  J. K. Bennett,et al.  An approach to switching control beyond nearest neighbor rules , 2006, 2006 American Control Conference.

[76]  Todd D. Murphey,et al.  A method of cooperative control using occasional non-local interactions , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..

[77]  Magnus Egerstedt,et al.  Role-Assignment in Multi-Agent Coordination , 2006 .

[78]  J. Cortés Characterizing robust coordination algorithms via proximity graphs and set-valued maps , 2006, 2006 American Control Conference.

[79]  Pradipta De,et al.  MiNT-m: an autonomous mobile wireless experimentation platform , 2006, MobiSys '06.