DEVELOPMENT AND IMPLEMENTATION OF ALGORITHMS IN A POPULATION OF COOPERATIVE AUTONOMOUS MOBILE ROBOTS

An increase in the number of mobile robot users has lead to the design and implementation of cooperati ve autonomous mobile robots. Autonomous robots require the ability to build maps of an unknown environment while simultaneously using these maps for navigatio n. The main factor in multiple mobile robots is tha t a team of smaller and simpler mobile robots can outpe rform a single, large and complex robot. The paper treats localization and map building as a joint probability, i.e. while robots navigate they localize and build local maps. These local maps from each ro bot in the team are fused into a global map at some instances during navigation. Cooperative simultaneo us localization and map building (C-SLAM) implemented by Extended Kalman Filter (EKF) algorithms are proposed towards task manipulation in a multirobot set up. The article entails modelling a multiple mobile rob ot system, in order to understand robot population communication and cooperation within an operational environment.

[1]  John J. Leonard,et al.  Adaptive Mobile Robot Navigation and Mapping , 1999, Int. J. Robotics Res..

[2]  Stergios I. Roumeliotis,et al.  Performance Bounds for Cooperative Simultaneous Localization and Mapping (C-SLAM) , 2005, Robotics: Science and Systems.

[3]  Stefan B. Williams.  Efficient Solutions to Autonomous Mapping and Navigation Problems , 2009 .

[4]  Stefan B. Williams,et al.  Constrained Initialization of the Simultaneous Localization and Mapping Algorithm , 2003, Int. J. Robotics Res..

[5]  John J. Leonard,et al.  Stochastic mapping frameworks , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[6]  Wolfram Burgard,et al.  Experiences with an Interactive Museum Tour-Guide Robot , 1999, Artif. Intell..

[7]  Henrik I. Christensen,et al.  Simultaneous localization and mapping in domestic environments , 2001, Conference Documentation International Conference on Multisensor Fusion and Integration for Intelligent Systems. MFI 2001 (Cat. No.01TH8590).

[8]  Gregory Dudek,et al.  Multi-robot cooperative localization: a study of trade-offs between efficiency and accuracy , 2002, IEEE/RSJ International Conference on Intelligent Robots and Systems.

[9]  Hugh F. Durrant-Whyte,et al.  A solution to the simultaneous localization and map building (SLAM) problem , 2001, IEEE Trans. Robotics Autom..

[10]  Randall Smith,et al.  Estimating Uncertain Spatial Relationships in Robotics , 1987, Autonomous Robot Vehicles.

[11]  Lynne E. Parker,et al.  Current State of the Art in Distributed Autonomous Mobile Robotics , 2000 .

[12]  Ryo Kurazume,et al.  Cooperative positioning with multiple robots , 1994, Proceedings of the 1994 IEEE International Conference on Robotics and Automation.

[13]  Lynne E. Parker,et al.  Distributed Cooperative Outdoor Multirobot Localization and Mapping , 2004 .

[14]  Matthew R. Walter,et al.  An Experimental investigation of cooperative SLAM , 2004 .

[15]  Vijay Kumar,et al.  Cooperative localization and control for multi-robot manipulation , 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).

[16]  John J. Leonard,et al.  Cooperative concurrent mapping and localization , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).