{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/73360"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/73360","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"Robot Autonomous Fire Location using a Weighted Probability Algorithm","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.","abstract_html":"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.","abstract_has_math":false,"creators":["Nogales, Chris Lorena"],"institution":"Virginia Tech","degree_name":"Master of Science","degree_level":"masters","degree_discipline":"Computer Engineering","degree_department":"Electrical and Computer Engineering","school":null,"contributors":[],"advisors":[],"committee_chairs":["Abbott, A. Lynn","Lattimer, Brian Y."],"committee_members":["Tokekar, Pratap"],"year":2016,"date_issued":"2016-11-01","date_published":"2016-11-01","updated_at":"2026-07-22T22:19:45Z","subjects":["autonomy","perception","Machine learning","firefighting robot"],"languages":[],"rights":["In Copyright"],"rights_urls":["http://rightsstatements.org/vocab/InC/1.0/"],"identifier_entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["vt_gsexam:8915"],"render_values":[{"text":"vt_gsexam:8915","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/10919/73360","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.committeechair","label":"Committee Chair","values":["Abbott, A. Lynn","Lattimer, Brian Y."]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Tokekar, Pratap"]},{"key":"dc:contributor.department","label":"Department","values":["Electrical and Computer Engineering"]},{"key":"dc:creator","label":"Author","values":["Nogales, Chris Lorena"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2016-11-02T08:00:37Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2016-11-02T08:00:37Z"]},{"key":"dc:date.issued","label":"Date","values":["2016-11-01"]},{"key":"dc:publisher","label":"Institution","values":["Virginia Tech"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["masters"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["Virginia Polytechnic Institute and State University"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["autonomy","perception","Machine learning","firefighting robot"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["In Copyright"]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://rightsstatements.org/vocab/InC/1.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["vt_gsexam:8915"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/10919/73360"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["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."]},{"key":"dc:description.abstractgeneral","label":"General Abstract","values":["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."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Master of Science"]},{"key":"dc:format.medium","label":"Dc Format Medium","values":["ETD"]},{"key":"dc:title","label":"Title","values":["Robot Autonomous Fire Location using a Weighted Probability Algorithm"]}]}],"canonical_facts":{"dc:contributor.committeechair":["Abbott, A. Lynn","Lattimer, Brian Y."],"dc:contributor.committeemember":["Tokekar, Pratap"],"dc:contributor.department":["Electrical and Computer Engineering"],"dc:creator":["Nogales, Chris Lorena"],"dc:date.accessioned":["2016-11-02T08:00:37Z"],"dc:date.available":["2016-11-02T08:00:37Z"],"dc:date.issued":["2016-11-01"],"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."],"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."],"dc:description.degree":["Master of Science"],"dc:format.medium":["ETD"],"dc:identifier.other":["vt_gsexam:8915"],"dc:identifier.uri":["http://hdl.handle.net/10919/73360"],"dc:publisher":["Virginia Tech"],"dc:rights":["In Copyright"],"dc:rights.uri":["http://rightsstatements.org/vocab/InC/1.0/"],"dc:subject":["autonomy","perception","Machine learning","firefighting robot"],"dc:title":["Robot Autonomous Fire Location using a Weighted Probability Algorithm"],"dc:type":["Thesis"],"thesis:degree_discipline":["Computer Engineering"],"thesis:degree_level":["masters"],"thesis:degree_name":["Master of Science"],"thesis:institution_name":["Virginia Polytechnic Institute and State University"]},"updated_at":"2026-07-22T22:19:45Z"}