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 |