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Communication Dans Un Congrès Année : 2012

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

Résumé

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 understanding of space, using which it can infer where to perform planned tasks in a manner that mimics human behavior. We assess the situation awareness of rescue workers 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 mapping " as an approach to identify regions in the USAR environment where planned tasks are likely to be optimally achievable. The system is deployed and evaluated in a simulated rescue scenario.
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Dates et versions

hal-01143134 , version 1 (17-04-2015)

Identifiants

  • HAL Id : hal-01143134 , version 1

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Shanker Keshavdas, Hendrik Zender, Geert Kruijff, Ming Liu, Francis Colas. Functional Mapping: Spatial Inferencing to Aid Human-Robot Rescue Efforts in Unstructured Disaster Environments. 2012 AAAI Spring Symposium on Designing Intelligent Robots, 2012, Stanford, United States. ⟨hal-01143134⟩
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