Robot Autonomous Fire Location using a Weighted Probability Algorithm
dc.contributor.author | Nogales, Chris Lorena | en |
dc.contributor.committeechair | Abbott, A. Lynn | en |
dc.contributor.committeechair | Lattimer, Brian Y. | en |
dc.contributor.committeemember | Tokekar, Pratap | en |
dc.contributor.department | Electrical and Computer Engineering | en |
dc.date.accessioned | 2016-11-02T08:00:37Z | en |
dc.date.available | 2016-11-02T08:00:37Z | en |
dc.date.issued | 2016-11-01 | en |
dc.description.abstract | Finding a fire inside of a structure without knowing its conditions poses a dangerous threat to the safety of firefighters. As a result, robots are being explored to increase awareness of the conditions inside structures before having firefighter enter. This thesis presents a method that autonomously guides a robot to the location of a fire inside a structure. The method uses classification of fire, smoke, and other fire environment objects to calculate a weighted probability. Weighted probability is a measurement that indicates the probability that a given region on an infra-red image will lead to fire. This method was tested on large-scale fire videos with a robot moving towards a fire and it is also compared to following the highest temperatures on the image. Sending a robot to find a fire has the potential to save the lives of firefighters. | en |
dc.description.abstractgeneral | Finding a fire inside of a structure without knowing its conditions poses a dangerous threat to the safety of firefighters. As a result, robots are being explored to increase awareness of the conditions inside structures before having firefighter enter. This thesis presents a method that autonomously guides a robot to the location of a fire inside a structure. The method uses classification of fire, smoke, and other fire environment objects to calculate a weighted probability. Weighted probability is a measurement that indicates the probability that a given region on an infra-red image will lead to fire. This method was tested on large-scale fire videos with a robot moving towards a fire and it is also compared to following the highest temperatures on the image. Sending a robot to find a fire has the potential to save the lives of firefighters. | en |
dc.description.degree | Master of Science | en |
dc.format.medium | ETD | en |
dc.identifier.other | vt_gsexam:8915 | en |
dc.identifier.uri | http://hdl.handle.net/10919/73360 | en |
dc.publisher | Virginia Tech | en |
dc.rights | In Copyright | en |
dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | en |
dc.subject | autonomy | en |
dc.subject | perception | en |
dc.subject | Machine learning | en |
dc.subject | firefighting robot | en |
dc.title | Robot Autonomous Fire Location using a Weighted Probability Algorithm | en |
dc.type | Thesis | en |
thesis.degree.discipline | Computer Engineering | en |
thesis.degree.grantor | Virginia Polytechnic Institute and State University | en |
thesis.degree.level | masters | en |
thesis.degree.name | Master of Science | en |
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