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, USA (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.