World Modeling in Disaster Environments with Constructive Self-Organizing Maps for Autonomous Search and Rescue Robots

This paper proposes a novel approach for a Constructive Self-Organizing Map (SOM) based world modeling for search and rescue operations in disaster environments. In our approach, nodes of the self organizing network consist of victim and waypoint classes where victim denotes a human being waiting to be rescued and waypoint denotes a free space that can be reached from the entrance of debris. The proposed approach performed better than traditional selforganizing maps in terms of both the accuracy of the output and the learning speed. In this paper the detailed explanation of the approach and some experimental results are given.