Functional Mapping: Spatial Inferencing to aid Human-Robot Rescue Efforts in Unstructured Disaster Environments

Shanker Keshavdas, Hendrik Zender, Geert-Jan Kruijff, M. Liu, F. Colas

In: Proceedings of the 2012 AAAI Spring Symposium on Designing Intelligent Robots. AAAI Spring Symposium (AAAI SSS-2012) AAAI Spring Symposium: Designing Intelligent Robots March 26-28 Stanford CA United States AAAI Press 2012.


In this paper we examine the case of a mobile robot that is part of a human-robot urban search and rescue (USAR) team. During USAR scenarios, we would like the robot to have a geometrical-functional understand- ing of space, using which it can infer where to perform planned tasks in a manner that mimics human behav- ior. We assess the situation awareness of rescue work- ers during a simulated USAR scenario and use this as an empirical basis to build our robot's spatial model. Based upon this spatial model, we present "functional map- ping"; as an approach to identify regions in the USAR environment where planned tasks are likely to be opti- mally achievable. The system is deployed and evaluated in a simulated rescue scenario.


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FunctionalMappingAAAI2012.pdf (pdf, 2 MB )

Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence