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

Keshavdas, Shanker (German Center for Artificial Intelligence (DFKI)) | Zender, Hendrik (German Center for Artificial Intelligence (DFKI)) | Kruijff, Geert-Jan M. (German Center for Artificial Intelligence (DFKI)) | Liu, Ming (Eudgenoessische Technische Hochschule) | Colas, Francis (Eudgenoessische Technische Hochschule)

AAAI Conferences 

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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