Robot Autonomous Fire Location using a Weighted Probability Algorithm

dc.contributor.authorNogales, Chris Lorenaen
dc.contributor.committeechairAbbott, A. Lynnen
dc.contributor.committeechairLattimer, Brian Y.en
dc.contributor.committeememberTokekar, Pratapen
dc.contributor.departmentElectrical and Computer Engineeringen
dc.date.accessioned2016-11-02T08:00:37Zen
dc.date.available2016-11-02T08:00:37Zen
dc.date.issued2016-11-01en
dc.description.abstractFinding 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.degreeMaster of Scienceen
dc.format.mediumETDen
dc.identifier.othervt_gsexam:8915en
dc.identifier.urihttp://hdl.handle.net/10919/73360en
dc.publisherVirginia Techen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectautonomyen
dc.subjectperceptionen
dc.subjectMachine learningen
dc.subjectfirefighting roboten
dc.titleRobot Autonomous Fire Location using a Weighted Probability Algorithmen
dc.typeThesisen
thesis.degree.disciplineComputer Engineeringen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.levelmastersen
thesis.degree.nameMaster of Scienceen
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