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dc.contributor.authorStarr, Joseph Wesleyen_US
dc.date.accessioned2016-12-21T09:02:14Z
dc.date.available2016-12-21T09:02:14Z
dc.date.issued2016-01-07en_US
dc.identifier.othervt_gsexam:7005en_US
dc.identifier.urihttp://hdl.handle.net/10919/73780
dc.description.abstractThe field of robotics has advanced to the point where robots are being developed for use in fire environments to perform firefighting tasks. These environments contain varying levels of fire and smoke, both of which obstruct robotic perception sensors. In order to effectively use robots in fire environments, the issue of perception in the presence of smoke and fire needs to be addressed. The goal of this research was to address the problem of perception, specifically rangefinding, in fire smoke environments. A series of tests were performed in fire smoke filled environments to evaluate the performance of different commercial rangefinders and cameras as well as a long-wavelength infrared (LWIR) stereo vision system developed in this research. The smoke was varied from dense, low temperature smoke to light, high temperature smoke for evaluation in a range of conditions. Through small-scale experiments on eleven different sensors, radar and LWIR cameras outperformed other perception sensors within both smoke environments. A LWIR stereo vision system was developed for rangefinding and compared to radar, LIDAR, and visual stereo vision in large-scale testing, demonstrating the ability of LWIR stereo vision to rangefind in dense smoke when LIDAR and visual stereo vision fail. LWIR stereo vision was further developed for improved rangefinding in fire environments. Intensity misalignment between cameras and stereo image filtering were addressed quantitatively. Tests were performed with approximately isothermal scenes and thermally diverse scenes to select subsystem methods. In addition, the effects of image filtering on feature distortion were assessed. Rangefinding improvements were quantified with comparisons to ground truth data. Improved perception in varying levels of clear and smoke conditions was developed through sensor fusion of LWIR stereo vision and a spinning LIDAR. The data were fused in a multi-resolution 3D voxel domain using evidential theory to model occupied and free space states. A heuristic method was presented to separate significantly attenuated LIDAR returns from low-attenuation returns. Sensor models were developed for both return types and LWIR stereo vision. The fusion system was tested in a range of conditions to demonstrate its ability for improved performance over individual sensor use in fire environments.en_US
dc.format.mediumETDen_US
dc.publisherVirginia Techen_US
dc.rightsThis item is protected by copyright and/or related rights. Some uses of this item may be deemed fair and permitted by law even without permission from the rights holder(s), or the rights holder(s) may have licensed the work for use under certain conditions. For other uses you need to obtain permission from the rights holder(s).en_US
dc.subjectLong-wavelength infrareden_US
dc.subjectthermal infrareden_US
dc.subjectstereo visionen_US
dc.subjectfireen_US
dc.subjectsmokeen_US
dc.subjectsensor fusionen_US
dc.subjectLIDARen_US
dc.titleRangefinding in Fire Smoke Environmentsen_US
dc.typeDissertationen_US
dc.contributor.departmentMechanical Engineeringen_US
dc.description.degreePh. D.en_US
thesis.degree.namePh. D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen_US
thesis.degree.disciplineMechanical Engineeringen_US
dc.contributor.committeechairLeonessa, Alexanderen_US
dc.contributor.committeechairLattimer, Brian Y.en_US
dc.contributor.committeememberWicks, Alfred L.en_US
dc.contributor.committeememberStilwell, Daniel J.en_US
dc.contributor.committeememberLee, Daniel D.en_US


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