Using a sensor network for distributed multi-robot task allocation

We present a multi field distributed in-network task allocation (DINTA-MF) algorithm for online multi-robot task allocation (OMRTA) where tasks are allocated explicitly to robots by a pre-deployed, static sensor network. The idea of DINTA-MF is to compute several assignment fields in the sensor network and then distributively assign fields to different robots. Experimental results with a simulated alarm scenario show that our approach is able to compute solutions to the OMRTA problem in a distributed fashion and arguably in an optimal way. We compared DINTA-MF with a simpler implementation (DINTA), which uses one assignment field. The data show that DINTA-MF outperforms DINTA as the number of robots increases.

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

[2]  Maja J. Mataric,et al.  Multi-robot task allocation: analyzing the complexity and optimality of key architectures , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[3]  Gaurav S. Sukhatme,et al.  Efficient exploration without localization , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[4]  David Chapman,et al.  Planning for Conjunctive Goals , 1987, Artif. Intell..

[5]  Michael A. Bender,et al.  The power of a pebble: exploring and mapping directed graphs , 1998, STOC '98.

[6]  Bala Kalyanasundaram,et al.  Online Weighted Matching , 1993, J. Algorithms.

[7]  J. Walrand,et al.  Distributed Dynamic Programming , 2022 .

[8]  Lynne E. Parker,et al.  ALLIANCE: an architecture for fault tolerant multirobot cooperation , 1998, IEEE Trans. Robotics Autom..

[9]  Maja J. Mataric,et al.  Broadcast of Local Elibility for Multi-Target Observation , 2000, DARS.

[10]  Michael Jenkin,et al.  Robotic exploration as graph construction , 1991, IEEE Trans. Robotics Autom..

[11]  Sven Koenig,et al.  Trail-laying robots for robust terrain coverage , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[12]  Sven Koenig,et al.  Complexity Analysis of Real-Time Reinforcement Learning , 1992, AAAI.

[13]  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).

[14]  Gaurav S. Sukhatme,et al.  Coverage, Exploration and Deployment by a Mobile Robot and Communication Network , 2003, Telecommun. Syst..

[15]  Deborah Estrin,et al.  Time synchronization for wireless sensor networks , 2001, Proceedings 15th International Parallel and Distributed Processing Symposium. IPDPS 2001.

[16]  Qun Li,et al.  Distributed algorithms for guiding navigation across a sensor network , 2003, MobiCom '03.

[17]  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).

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

[19]  Tamio Arai,et al.  Distributed Autonomous Robotic Systems 3 , 1998 .

[20]  Rachid Alami,et al.  M+: a scheme for multi-robot cooperation through negotiated task allocation and achievement , 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).

[21]  Gaurav S. Sukhatme,et al.  LOST: localization-space trails for robot teams , 2002, IEEE Trans. Robotics Autom..

[22]  Gaurav S. Sukhatme,et al.  Distributed multi-robot task allocation for emergency handling , 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).