DFKI-LT - Functional Mapping: Spatial Inferencing to aid Human-Robot Rescue Efforts in Unstructured Disaster Environments
Functional Mapping: Spatial Inferencing to aid Human-Robot Rescue Efforts in Unstructured Disaster Environments
Proceedings of the 2012 AAAI Spring Symposium on Designing Intelligent Robots, Stanford, CA, United States, AAAI Press, Stanford University, 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.
Files: BibTeX, FunctionalMappingAAAI2012.pdf, 4318