A Scalable , Platform-Independent SLAM System for Urban Search and Rescue

Robot systems see increasing use outside the field of automation engineering, where they were first introduced. To solve complex tasks in unknown environments, autonomous systems need a model of their environment. An example of such a complex task are Urban Search and Rescue (USAR) scenarios. In the scope of this work, a platform independent and scalable system for simultaneous localization and mapping (SLAM) for autonomous and semiautonomous robots was developed, enabling these platforms to generate 2D maps of USAR and other environments using a laser scanner. A particle filter and scan registration approach were implemented. Experiments show that a combination of both approaches yields the best results. The system described in this work was deployed successfully on an Unmanned Ground Vehicle (UGV) in the Robot Rescue League of the international robotics competition RoboCup 2009.

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