Cognitive Map Merging For Multi-Robot Navigation

In this paper we investigate a map-building strategy based on geometric and topological information about the environment, acquired through sonar sensors and odometric actuator. To reduce robot individual exploration needs, a framework based on multi-robot map acquisition is proposed, where each robot executes a map building algorithm and performs exploration in the environment. The current global map is built based on the merging of overlapping regions among the previously cognitive maps. A brief description of the on-going research and the results obtained is also provided.

[1]  Heekuck Oh,et al.  Neural Networks for Pattern Recognition , 1993, Adv. Comput..

[2]  Rüdiger Dillmann,et al.  Integration of topological and geometrical planning in a learning mobile robot , 1994, Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'94).

[3]  Viii Supervisor Sonar-Based Real-World Mapping and Navigation , 2001 .

[4]  Paul J. Besl,et al.  A Method for Registration of 3-D Shapes , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  Sebastian Thrun,et al.  Learning Maps for Indoor Mobile Robot Navigation. , 1996 .

[6]  José del R. Millán,et al.  Efficient learning of variable-resolution cognitive maps for autonomous indoor navigation , 1999, IEEE Trans. Robotics Autom..

[7]  Wesley H. Huang,et al.  Topological Map Merging , 2005, Int. J. Robotics Res..

[8]  William H. Press,et al.  Numerical Recipes in C, 2nd Edition , 1992 .

[9]  Sebastian Thrun,et al.  Robotic mapping: a survey , 2003 .

[10]  Geoffrey E. Hinton,et al.  Learning representations by back-propagating errors , 1986, Nature.