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)
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.
Mar-25-2012
- Country:
- Europe
- Germany (0.47)
- Switzerland > Zürich
- Zürich (0.14)
- Europe
- Industry:
- Government (0.66)
- Technology:
- Information Technology > Artificial Intelligence
- Cognitive Science > Problem Solving (0.94)
- Representation & Reasoning > Ontologies (1.00)
- Robots (1.00)
- Information Technology > Artificial Intelligence