{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/23101"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/23101","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"Multi-spectral System for Autonomous Robotic Location of Fires Indoors","abstract":"Autonomous firefighting platforms are being developed to support firefighters. One aspect of this is location of a fire inside a structure. A multi-spectral sensor platform and fire location algorithm was developed in this research to locate a fire indoors autonomously. The multi-spectral sensor platform used a long wavelength infrared (LWIR) camera and ultraviolet (UV) sensor. The LWIR camera was chosen for its ability to see through smoke, while the UV sensor was selected for its ability to discriminate between fires and non-fire hot objects. The fire location algorithm by radiation emission (FLARE) developed in this research used the multi-spectral sensor data to provide the robot heading angle toward the fire. The system was tested in a large-scale structural fire facility. A series of 20 different scenarios were used to evaluate the robustness of the system including different fuel types, structural features, non-fire hot objects, and potential robot positions within the enclosure. This demonstrated that FLARE could direct a robot towards the fire regardless of these variables. Directional fire discrimination was added to the platform by limiting the field of view of the UV sensor to that of the LWIR cameras. Three methods were evaluated to limit the field of view of a UV sensor. These included angled plate housing, bulb cover, and slit opening housing methods. The slit opening housing method was recommended for ease of implementation and size required to limit the field of view of the sensor to the desired value.","abstract_html":"Autonomous firefighting platforms are being developed to support firefighters. One aspect of this is location of a fire inside a structure. A multi-spectral sensor platform and fire location algorithm was developed in this research to locate a fire indoors autonomously. The multi-spectral sensor platform used a long wavelength infrared (LWIR) camera and ultraviolet (UV) sensor. The LWIR camera was chosen for its ability to see through smoke, while the UV sensor was selected for its ability to discriminate between fires and non-fire hot objects. The fire location algorithm by radiation emission (FLARE) developed in this research used the multi-spectral sensor data to provide the robot heading angle toward the fire. The system was tested in a large-scale structural fire facility. A series of 20 different scenarios were used to evaluate the robustness of the system including different fuel types, structural features, non-fire hot objects, and potential robot positions within the enclosure. This demonstrated that FLARE could direct a robot towards the fire regardless of these variables. Directional fire discrimination was added to the platform by limiting the field of view of the UV sensor to that of the LWIR cameras. Three methods were evaluated to limit the field of view of a UV sensor. These included angled plate housing, bulb cover, and slit opening housing methods. The slit opening housing method was recommended for ease of implementation and size required to limit the field of view of the sensor to the desired value.","abstract_has_math":false,"creators":["Keller, Brian Matthew"],"institution":"Virginia Tech","degree_name":"Master of Science","degree_level":"masters","degree_discipline":"Mechanical Engineering","degree_department":"Mechanical Engineering","school":null,"contributors":[],"advisors":[],"committee_chairs":["Lattimer, Brian Y."],"committee_members":["Leonessa, Alexander","Kochersberger, Kevin B."],"year":2013,"date_issued":"2013-05-26","date_published":"2013-05-26","updated_at":"2026-07-22T22:19:32Z","subjects":["Fire","Infrared","Ultraviolet","Firefighting","Autonomous"],"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:976"],"render_values":[{"text":"vt_gsexam:976","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/10919/23101","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.committeechair","label":"Committee Chair","values":["Lattimer, Brian Y."]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Leonessa, Alexander","Kochersberger, Kevin B."]},{"key":"dc:contributor.department","label":"Department","values":["Mechanical Engineering"]},{"key":"dc:creator","label":"Author","values":["Keller, Brian Matthew"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2013-05-27T08:00:17Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2013-05-27T08:00:17Z"]},{"key":"dc:date.issued","label":"Date","values":["2013-05-26"]},{"key":"dc:publisher","label":"Institution","values":["Virginia Tech"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Mechanical 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":["Fire","Infrared","Ultraviolet","Firefighting","Autonomous"]}]},{"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:976"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/10919/23101"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Autonomous firefighting platforms are being developed to support firefighters. One aspect of this is location of a fire inside a structure. A multi-spectral sensor platform and fire location algorithm was developed in this research to locate a fire indoors autonomously. The multi-spectral sensor platform used a long wavelength infrared (LWIR) camera and ultraviolet (UV) sensor. The LWIR camera was chosen for its ability to see through smoke, while the UV sensor was selected for its ability to discriminate between fires and non-fire hot objects. The fire location algorithm by radiation emission (FLARE) developed in this research used the multi-spectral sensor data to provide the robot heading angle toward the fire. The system was tested in a large-scale structural fire facility. A series of 20 different scenarios were used to evaluate the robustness of the system including different fuel types, structural features, non-fire hot objects, and potential robot positions within the enclosure. This demonstrated that FLARE could direct a robot towards the fire regardless of these variables. Directional fire discrimination was added to the platform by limiting the field of view of the UV sensor to that of the LWIR cameras. Three methods were evaluated to limit the field of view of a UV sensor. These included angled plate housing, bulb cover, and slit opening housing methods. The slit opening housing method was recommended for ease of implementation and size required to limit the field of view of the sensor to the desired value."]},{"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":["Multi-spectral System for Autonomous Robotic Location of Fires Indoors"]}]}],"canonical_facts":{"dc:contributor.committeechair":["Lattimer, Brian Y."],"dc:contributor.committeemember":["Leonessa, Alexander","Kochersberger, Kevin B."],"dc:contributor.department":["Mechanical Engineering"],"dc:creator":["Keller, Brian Matthew"],"dc:date.accessioned":["2013-05-27T08:00:17Z"],"dc:date.available":["2013-05-27T08:00:17Z"],"dc:date.issued":["2013-05-26"],"dc:description.abstract":["Autonomous firefighting platforms are being developed to support firefighters. One aspect of this is location of a fire inside a structure. A multi-spectral sensor platform and fire location algorithm was developed in this research to locate a fire indoors autonomously. The multi-spectral sensor platform used a long wavelength infrared (LWIR) camera and ultraviolet (UV) sensor. The LWIR camera was chosen for its ability to see through smoke, while the UV sensor was selected for its ability to discriminate between fires and non-fire hot objects. The fire location algorithm by radiation emission (FLARE) developed in this research used the multi-spectral sensor data to provide the robot heading angle toward the fire. The system was tested in a large-scale structural fire facility. A series of 20 different scenarios were used to evaluate the robustness of the system including different fuel types, structural features, non-fire hot objects, and potential robot positions within the enclosure. This demonstrated that FLARE could direct a robot towards the fire regardless of these variables. Directional fire discrimination was added to the platform by limiting the field of view of the UV sensor to that of the LWIR cameras. Three methods were evaluated to limit the field of view of a UV sensor. These included angled plate housing, bulb cover, and slit opening housing methods. The slit opening housing method was recommended for ease of implementation and size required to limit the field of view of the sensor to the desired value."],"dc:description.degree":["Master of Science"],"dc:format.medium":["ETD"],"dc:identifier.other":["vt_gsexam:976"],"dc:identifier.uri":["http://hdl.handle.net/10919/23101"],"dc:publisher":["Virginia Tech"],"dc:rights":["In Copyright"],"dc:rights.uri":["http://rightsstatements.org/vocab/InC/1.0/"],"dc:subject":["Fire","Infrared","Ultraviolet","Firefighting","Autonomous"],"dc:title":["Multi-spectral System for Autonomous Robotic Location of Fires Indoors"],"dc:type":["Thesis"],"thesis:degree_discipline":["Mechanical Engineering"],"thesis:degree_level":["masters"],"thesis:degree_name":["Master of Science"],"thesis:institution_name":["Virginia Polytechnic Institute and State University"]},"updated_at":"2026-07-22T22:19:32Z"}