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Robots for disaster management

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dc.contributor.author Van Eden, Beatrice
dc.contributor.author Rosman, Benjamin S
dc.date.accessioned 2018-08-09T11:01:16Z
dc.date.available 2018-08-09T11:01:16Z
dc.date.issued 2018-05
dc.identifier.citation Van Eden, B. and Rosman, B.S. 2018. Robots for disaster management. 2018 International Women in Science Without Borders (WiSWB)-Indaba, 22-23 March 2018, University of Johannesburg, Johannesburg, South Africa en_US
dc.identifier.isbn 978-0-620-78656-0
dc.identifier.uri https://researchspace.csir.co.za/dspace/handle/10204/10251
dc.identifier.uri http://wiswb2018.co.za/wp-content/uploads/2018/03/WISWB2018-ProgramBooklet.compressed.pdf
dc.identifier.uri http://hdl.handle.net/10204/10350
dc.description Paper presented at the 2018 International Women in Science Without Borders (WiSWB)-Indaba, 22-23 March 2018, University of Johannesburg, Johannesburg, South Africa en_US
dc.description.abstract The past years have seen many deadly natural disasters including hurricanes, earthquakes, flooding and landslides. Search and rescue efforts have saved numerous lives but numerous others were lost. At the same time, robotic technology is becoming more widespread, and brings with it the potential to assist in these search and rescue scenarios. Despite many impressive advances, robots still lack the ability to function as humans do in complex environments. Importantly, this includes being able to interpret and understand complexities of the world as humans do. This short paper explains our first steps towards better robot cognition, for use in search and rescue scenarios. To this end, we focus particularly on the ability to understand the current surroundings of the robot. Our setup involves collecting data from a mobile robot moving between three different settings, and using this to train a neural network to identify the current setting. The robot will then be able to roam around in an environment and identify the three settings, marking them on the map it creates of the environment. en_US
dc.language.iso en en_US
dc.relation.ispartofseries Worklist;21093
dc.subject Natural disasters en_US
dc.subject Disaster management en_US
dc.subject Robot cognition en_US
dc.title Robots for disaster management en_US
dc.type Conference Presentation en_US
dc.identifier.apacitation Van Eden, B., & Rosman, B. S. (2018). Robots for disaster management. http://hdl.handle.net/10204/10350 en_ZA
dc.identifier.chicagocitation Van Eden, Beatrice, and Benjamin S Rosman. "Robots for disaster management." (2018): http://hdl.handle.net/10204/10350 en_ZA
dc.identifier.vancouvercitation Van Eden B, Rosman BS, Robots for disaster management; 2018. http://hdl.handle.net/10204/10350 . en_ZA
dc.identifier.ris TY - Conference Presentation AU - Van Eden, Beatrice AU - Rosman, Benjamin S AB - The past years have seen many deadly natural disasters including hurricanes, earthquakes, flooding and landslides. Search and rescue efforts have saved numerous lives but numerous others were lost. At the same time, robotic technology is becoming more widespread, and brings with it the potential to assist in these search and rescue scenarios. Despite many impressive advances, robots still lack the ability to function as humans do in complex environments. Importantly, this includes being able to interpret and understand complexities of the world as humans do. This short paper explains our first steps towards better robot cognition, for use in search and rescue scenarios. To this end, we focus particularly on the ability to understand the current surroundings of the robot. Our setup involves collecting data from a mobile robot moving between three different settings, and using this to train a neural network to identify the current setting. The robot will then be able to roam around in an environment and identify the three settings, marking them on the map it creates of the environment. DA - 2018-05 DB - ResearchSpace DP - CSIR KW - Natural disasters KW - Disaster management KW - Robot cognition LK - https://researchspace.csir.co.za PY - 2018 SM - 978-0-620-78656-0 T1 - Robots for disaster management TI - Robots for disaster management UR - http://hdl.handle.net/10204/10350 ER - en_ZA


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