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A Semantic Interpreter for Multimodal and Multirobot Data
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering.
2016 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Huge natural disaster events can be so devastating that they often overwhelm human rescuers and yet, they seem to occur more often. The TRADR (Long-Term Human-Robot Teaming for Robot Assisted Disaster Response) research project aims at developing methodology for heterogeneous teams composed of human rescuers as well as ground and aerial robots. While the robots swarm the disaster sites, equipped with advanced sensors, they collect a huge amount row-data that cannot be processed efficiently by humans. Therefore, in the frame of the here presented work, a semantic interpreter has been developed that crawls through the raw data, using state of the art object detection algorithms to identify victim targets and extracts all kinds of information that is relevant for rescuers to plan their missions. Subsequently, this information is restructured by a reasoning process and then stored into a high-level database that can be queried accordingly and ensures data constancy.

Place, publisher, year, edition, pages
Keyword [en]
Semantic Interpreter, TRADR, Robot Assisted Disaster Response, Victim Detection
URN: urn:nbn:se:ltu:diva-36896OAI: diva2:1010377
Educational program
Space Engineering, master's level
Available from: 2016-10-03 Created: 2016-10-03 Last updated: 2016-10-03Bibliographically approved

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