Communication Aspects of Coordination in Robot Wireless Networks

obots coordinate among themselves to selectone of them to respond to an event reportedto one of the robots so that the communi-cation cost of selecting the best robot,response time, and cost of performing thetaskareminimized.Existingsolutionsareeithercen-tralized, assuming a complete graph, or based onfloodingwithindividualresponsestoarobotdeci-sion maker [simple auction protocol (SAP)],ignoring communication cost and response timebound. This article proposes auction aggregationprotocols (AAPs) for task assignment in multihopwireless robot networks. A robot collector leadsan auction and initiates a response tree construc-tion by transmitting the search message. Afterreceiving the message, each robot makes a deci-sion on whether to retransmit a search message,based on the estimated response cost of its robots,up to k-hops away. Robots wait to receive thebids from its children in the search tree. Then,robots aggregate responses by selecting the bestbidandforwarditbacktowardtherobotcollector(auctioning robot). When distance is used as thesole cost metrics, the traversal aggregation algo-rithm [routing with face traversal (RFT) —routingtoward the event with the traversal of the face con-tainingtheevent]canbeappliedandisanoptimalsolution. Several other protocols and theirenhancementsarealsodescribedhere.Multirobot systems (MRSs) are wellstudied in literature [1], and the focalpoint of the majority of MRS-relatedarticles is on coordination and coop-eration. The term networked roboticsemerged recently emphasizing that robotscan be connected by a wireless mediumforminga communication network.Thereare

[1]  Debasish Ghose,et al.  Team, Game, and Negotiation based Intelligent Autonomous UAV Task Allocation for Wide Area Applications , 2007, Innovations in Intelligent Machines.

[2]  Ivan Stojmenovic,et al.  On delivery guarantees of face and combined greedy-face routing in ad hoc and sensor networks , 2006, MobiCom '06.

[3]  Vijay Kumar,et al.  Distributed multi-robot task assignment and formation control , 2008, 2008 IEEE International Conference on Robotics and Automation.

[4]  Antidio Viguria,et al.  Upper-bound cost analysis of a market-based algorithm applied to the initial formation problem , 2007, 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[5]  Maja J. Mataric,et al.  Sold!: auction methods for multirobot coordination , 2002, IEEE Trans. Robotics Autom..

[6]  Nuzhet Atay,et al.  Mixed-Integer Linear Programming Solution to Multi-Robot Task Allocation Problem , 2006 .

[7]  Ayanna M. Howard,et al.  A Robotic Mobile Sensor Network for Achieving Scientific Measurements in Challenging Environments , 2008 .

[8]  Maria L. Gini,et al.  Auctions for task allocation to robots , 2006, IAS.

[9]  Marudachalam Dhanaraj,et al.  Energy Efficient Assignment of Events in Wireless Sensor and Mobile Actor Networks , 2006, 2006 14th IEEE International Conference on Networks.

[10]  Michail G. Lagoudakis,et al.  The Generation of Bidding Rules for Auction-Based Robot Coordination , 2005 .

[11]  Junku Yuh,et al.  The Status of Robotics , 2007, IEEE Robotics & Automation Magazine.

[12]  Ivan Stojmenovic,et al.  Routing with Guaranteed Delivery in Ad Hoc Wireless Networks , 1999, DIALM '99.

[13]  Nidhi Kalra,et al.  Market-Based Multirobot Coordination: A Survey and Analysis , 2006, Proceedings of the IEEE.

[14]  Deborah Estrin,et al.  GHT: a geographic hash table for data-centric storage , 2002, WSNA '02.

[15]  Yan Meng,et al.  Communication-Efficient Dynamic Task Scheduling for Heterogeneous Multi-Robot Systems , 2007, 2007 International Symposium on Computational Intelligence in Robotics and Automation.

[16]  Dario Pompili,et al.  Communication and Coordination in Wireless Sensor and Actor Networks , 2007, IEEE Transactions on Mobile Computing.