The 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. / Ph. D.

Approved for public release; distribution in unlimited. / Silicon Blocked Impurity Band (BIB) detectors are highly efficient, radiation-hardened photodetectors that operate in the range of 5-40 æm. To further extend BIB coverage to 40-350 æm, Ge and GaAs BIB detectors are under development; however, these new detectors face fabrication issues that have delayed their introduction. This thesis will describe the use of a numerical model to examine alternate operating modes for GaAs BIB detectors in order to bypass current fabrication issues. The numerical simulations provide an understanding of the fundamental physics that governs detector transport. The proposed alternatives to standard operation are created by reversing the detector's bias and varying the blocking layer thickness. Modeling indicates that reversing the bias on these detectors provides a larger signal current than standard configurations, while preserving the principal benefits gained from a multilayered device. At the same time, the alternate bias configuration allows for the use of thicker blocking layers, while preserving overall detector responsivity and reducing shot noise. This proposed new model of operation should allow for the relaxation of fabrication constraints without sacrificing the inherent benefits associated with BIB detectors. These devices are of potential interest for missile defense and terahertz surveillance applications. / Lieutenant Commander, United States Navy

Thermography is a non-destructive technique which uses infrared radiation to obtain the temperature distribution of an object. The technique is increasingly used in the pulp and paper industry. To convert the detected infrared radiation to a temperature, the emittance of the material must be known. For several influencing parameters the emittance of paper and board has not previously been studied in detail. This is partly due to the lack of emittance measurement methods that allow for studying the influence of these parameters. An angle-resolved goniometric method for measuring the infrared emittance of a material was developed in this thesis. The method is based on the reference emitter methodology, and uses commercial infrared cameras to determine the emittance. The method was applied to study the dependence on wavelength range, temperature, observation angle, moisture ratio, sample composition, and sample structure of the emittance of paper and board samples. It was found that the emittance varied significantly with wavelength range, observation angle and moisture ratio. The emittance was significantly higher in the LWIR (Long-Wavelength Infrared) range than in the MWIR (Mid-Wavelength Infrared) range. The emittance was approximately constant up to an observation angle of 60° in the MWIR range and 70° in the LWIR range, respectively. After that it started to decrease. The emittance of moist samples was significantly higher than that of dry samples. The influence of moisture ratio on the emittance could be estimated based on the moisture ratio of the sample, and the emittance of pure water and dry material, respectively. The applicability of measured emittance values was demonstrated in an investigation of the mechanical properties of sack paper samples. An infrared camera was applied to monitor the generation of heat during a tensile test of a paper sample. It was found that the observed increase in thermal energy at the time of rupture corresponded well to the value of the elastic energy stored in the sample just prior to rupture. The measured emittance value provided an increased accuracy in the thermal energy calculation based on the infrared images. / <p>QC 20121121</p>