Robot Autonomous Fire Location using a Weighted Probability Algorithm

Nogales, Chris Lorena

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