The interplay between networks and robotics: networked robots and robotic routers

In this work, we explore the interplay between robotics and networks. Robots can benefit from an embedded network and also the network can benefit from the mobility of the robots. We investigate the design space where the application is oriented towards robotics or networking, considering how much information about the environment is provided and what the sensing capabilities are. At one end, the robots can benefit from the resources of an environment-embedded network, in which robot sensing and communication is enhanced by the network. We consider the design and implementation of practical pursuit-evasion games with networked robots, where a communication network provides sensing-at-a-distance as well as a communication backbone that enables tighter coordination between pursuers. Using the theory of zero-sum games, we develop an algorithm that computes the minimal completion time strategy for multi-pursuit multi-evasion when all players make optimal decisions based on complete knowledge. We then describe the design of a real-world mobile robot-based pursuit evasion game. We validate our algorithms by experiments in a moderate-scale testbed in a challenging office environment. We then show that the network can also benefit from Robotics by taking advance of micro and macro motion. Robots can mitigate multi-path fading. We design a system that allows robots to cooperate and improve the real-world network throughput via a distributed cooperation framework. A mobile wireless network can also be quickly and autonomously deployed in urban search and rescue efforts, forming a communication substrate. We study the problem of determining the minimum number of mobile robots and how to position them so all clients are connected. Our approach to the problem is based on virtual potential fields where we treat each client as a virtual charged particle. We validate our algorithm with physical robots in an indoor environment and demonstrate that we are able to get feasible solutions.

[1]  Jingyuan Li,et al.  Automatic and robust breadcrumb system deployment for indoor firefighter applications , 2010, MobiSys '10.

[2]  Qun Li,et al.  Navigation protocols in sensor networks , 2005, TOSN.

[3]  Gaurav S. Sukhatme,et al.  Constrained coverage for mobile sensor networks , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[4]  Rabin K. Patra,et al.  Routing in a delay tolerant network , 2004, SIGCOMM '04.

[5]  Sampath Kannan,et al.  Randomized pursuit-evasion in a polygonal environment , 2005, IEEE Transactions on Robotics.

[6]  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).

[7]  Konstantinos Psounis,et al.  The achievable rate region of 802.11-scheduled multihop networks , 2009, TNET.

[8]  M. Ani Hsieh,et al.  Towards the deployment of a mobile robot network with end-to-end performance guarantees , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..

[9]  Gaurav S. Sukhatme,et al.  The Design and Analysis of an Efficient Local Algorithm for Coverage and Exploration Based on Sensor Network Deployment , 2007, IEEE Transactions on Robotics.

[10]  Milind Tambe,et al.  Distributed Sensor Networks: A Multiagent Perspective , 2003 .

[11]  S. Shankar Sastry,et al.  Tracking and Coordination of Multiple Agents Using Sensor Networks: System Design, Algorithms and Experiments , 2007, Proceedings of the IEEE.

[12]  Benjamin Kuipers,et al.  A robot exploration and mapping strategy based on a semantic hierarchy of spatial representations , 1991, Robotics Auton. Syst..

[13]  Weixiong Zhang,et al.  An analysis and application of distributed constraint satisfaction and optimization algorithms in sensor networks , 2003, AAMAS '03.

[14]  Connections between cooperative control and potential games illustrated on the consensus problem , 2007, 2007 European Control Conference (ECC).

[15]  Karl Henrik Johansson,et al.  Using robot mobility to exploit multipath fading , 2009, IEEE Wireless Communications.

[16]  Radhika Nagpal,et al.  Robust and Self-Repairing Formation Control for Swarms of Mobile Agents , 2005, AAAI.

[17]  Joel M. Esposito,et al.  Maintaining wireless connectivity constraints for swarms in the presence of obstacles , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..

[18]  David Wetherall,et al.  802.11 with multiple antennas for dummies , 2010, CCRV.

[19]  Martin Aigner,et al.  A game of cops and robbers , 1984, Discret. Appl. Math..

[20]  Leonidas J. Guibas,et al.  Visibility-Based Pursuit-Evasion in a Polygonal Environment , 1997, WADS.

[21]  J. Seybold Introduction to RF Propagation , 2005 .

[22]  Volkan Isler,et al.  Robotic routers , 2008, 2008 IEEE International Conference on Robotics and Automation.

[23]  Jirí Sgall Solution of David Gale's lion and man problem , 2001, Theor. Comput. Sci..

[24]  Kevin R. Fall,et al.  A delay-tolerant network architecture for challenged internets , 2003, SIGCOMM '03.

[25]  M. Ani Hsieh,et al.  Constructing radio signal strength maps with multiple robots , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[26]  Gaurav S. Sukhatme,et al.  An Incremental Self-Deployment Algorithm for Mobile Sensor Networks , 2002, Auton. Robots.

[27]  Kameswari Chebrolu,et al.  Long-distance 802.11b links: performance measurements and experience , 2006, MobiCom '06.

[28]  S. Shankar Sastry,et al.  Probabilistic pursuit-evasion games: theory, implementation, and experimental evaluation , 2002, IEEE Trans. Robotics Autom..

[29]  David Tse,et al.  Mobility increases the capacity of ad hoc wireless networks , 2002, TNET.

[30]  Alain Quilliot,et al.  A short note about pursuit games played on a graph with a given genus , 1985, J. Comb. Theory, Ser. B.

[31]  T. D. Parsons,et al.  Pursuit-evasion in a graph , 1978 .

[32]  Erik Blasch,et al.  Formation control in multi-player pursuit evasion game with superior evaders , 2007, SPIE Defense + Commercial Sensing.

[33]  Nicholas R. Jennings,et al.  Decentralised coordination of low-power embedded devices using the max-sum algorithm , 2008, AAMAS.

[34]  Deborah Estrin,et al.  The Tenet architecture for tiered sensor networks , 2006, SenSys '06.

[35]  Wendy J. Myrvold,et al.  Practical toroidality testing , 1997, SODA '97.

[36]  B. Alspach SEARCHING AND SWEEPING GRAPHS: A BRIEF SURVEY , 2006 .

[37]  Makoto Yokoo,et al.  DCOPs meet the realworld: exploring unknown reward matrices with applications to mobile sensor networks , 2009, IJCAI 2009.

[38]  Wei-Min Shen,et al.  TENTACLES: Self-configuring robotic radio networks in unknown environments , 2009, 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[39]  Vijay Kumar,et al.  Connectivity management in mobile robot teams , 2008, 2008 IEEE International Conference on Robotics and Automation.

[40]  B. Intrigila,et al.  On the Cop Number of a Graph , 1993 .

[41]  Roger Mailler,et al.  Commbots: Distributed control of mobile communication relays , 2006 .

[42]  Francesco Bullo,et al.  Distributed Control of Robotic Networks , 2009 .

[43]  Sourabh Bhattacharya,et al.  Motion Strategies for Surveillance , 2007, Robotics: Science and Systems.

[44]  Ulrich Pferschy Solution methods and computational investigations for the Linear Bottleneck Assignment Problem , 2007, Computing.

[45]  Jonathan M. Smith,et al.  RF-mobility gain: concept, measurement campaign, and exploitation , 2009, IEEE Wireless Communications.

[46]  Peter Winkler,et al.  Vertex-to-vertex pursuit in a graph , 1983, Discret. Math..

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

[48]  Yi Li,et al.  Predictable performance optimization for wireless networks , 2008, SIGCOMM '08.

[49]  Klaus Schilling,et al.  Commanding mobile robots via wireless ad-hoc networks — A comparison of four ad-hoc routing protocol implementations , 2008, 2008 IEEE International Conference on Robotics and Automation.

[50]  Theodore S. Rappaport,et al.  Wireless communications - principles and practice , 1996 .

[51]  Tucker R. Balch,et al.  Physical Path Planning Using the GNATs , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[52]  Maja J. Mataric,et al.  Integration of representation into goal-driven behavior-based robots , 1992, IEEE Trans. Robotics Autom..

[53]  Pradeep K. Khosla,et al.  Real-time obstacle avoidance using harmonic potential functions , 1991, IEEE Trans. Robotics Autom..

[54]  Robert Morris,et al.  Link-level measurements from an 802.11b mesh network , 2004, SIGCOMM 2004.

[55]  Chenyang Lu,et al.  Adaptive Embedded Roadmaps For Sensor Networks , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[56]  Edward W. Knightly,et al.  Assessment of urban-scale wireless networks with a small number of measurements , 2008, MobiCom '08.

[57]  Gaurav S. Sukhatme,et al.  Coverage, Exploration and Deployment by a Mobile Robot and Communication Network , 2004, Telecommun. Syst..

[58]  Alejandro Sarmiento,et al.  Surveillance Strategies for a Pursuer with Finite Sensor Range , 2007, Int. J. Robotics Res..

[59]  Peter Steenkiste,et al.  Efficient channel-aware rate adaptation in dynamic environments , 2008, MobiSys '08.

[60]  A. Volgenant,et al.  A shortest augmenting path algorithm for dense and sparse linear assignment problems , 1987, Computing.

[61]  Karl Henrik Johansson,et al.  An experimental study of exploiting multipath fading for robot communications , 2007, Robotics: Science and Systems.

[62]  Nikolaus Correll,et al.  Ad-hoc wireless network coverage with networked robots that cannot localize , 2009, 2009 IEEE International Conference on Robotics and Automation.

[63]  Rainer E. Burkard,et al.  Linear Assignment Problems and Extensions , 1999, Handbook of Combinatorial Optimization.

[64]  Peter I. Corke,et al.  Localization and Navigation Assisted by Networked Cooperating Sensors and Robots , 2005, Int. J. Robotics Res..

[65]  Dorit S. Hochbaum,et al.  Heuristics for the fixed cost median problem , 1982, Math. Program..

[66]  Helmut Bölcskei,et al.  An overview of MIMO communications - a key to gigabit wireless , 2004, Proceedings of the IEEE.

[67]  Milind Tambe,et al.  Quality Guarantees on k-Optimal Solutions for Distributed Constraint Optimization Problems , 2007, IJCAI.

[68]  Kang G. Shin,et al.  On accurate measurement of link quality in multi-hop wireless mesh networks , 2006, MobiCom '06.

[69]  Peter Norvig,et al.  Artificial Intelligence: A Modern Approach , 1995 .

[70]  Gaurav S. Sukhatme,et al.  Deployment and Connectivity Repair of a Sensor Net with a Flying Robot , 2004, ISER.

[71]  Edward M. Reingold,et al.  The complexity of pursuit on a graph , 1995 .

[72]  Warren A. Cheung,et al.  Constrained Pursuit-Evasion Problems in the Plane , 2005 .

[73]  Richard J. Nowakowski,et al.  A game of cops and robbers played on products of graphs , 1998, Discret. Math..

[74]  Philippe Jacquet,et al.  Optimized Link State Routing Protocol (OLSR) , 2003, RFC.

[75]  Genshe Chen,et al.  A decentralized approach to pursuer-evader games with multiple superior evaders , 2006, 2006 IEEE Intelligent Transportation Systems Conference.