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Evidential Sensor Fusion of Long-Wavelength Infrared Stereo Vision and 3D-LIDAR for Rangefinding in Fire Environments

机译:长波长红外立体视觉和3D-LIDAR的证据传感器融合,用于火灾环境中的测距

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A method of sensor fusion was developed to combine long-wavelength infrared (LWIR) stereo vision and a spinning LIDAR for improved rangefinding in smoke-obscured environments. This method allows rangefinding in clear and smoke conditions, relying on LIDAR's high accuracy in clear conditions and the perception ability of LWIR cameras in smoke. Sensor data were combined using evidential (Dempster-Shafer) theory in a 3D multi-resolution voxel domain for occupied and free space states. A heuristic method was produced for separating significantly attenuated and low-attenuation LIDAR returns using return intensity and distance. A sensor model was developed to apply free space state information from LIDAR high-attenuation returns. Sensor models were developed for applying occupied and free space state information from LIDAR low-attenuation returns and from LWIR stereo vision points. The fusion method was evaluated in two fire environments: a room-hallway scenario with a range of clear to dense-smoke conditions and a shipboard fire scenario. Room-hallway tests were evaluated by assessing performance against baseline rangefinding. For the occupied state, the fusion method and LIDAR are within typically 5% to 10% for clear conditions, and the fusion method is more accurate than the LIDAR by typically 5% to 10% for smoke conditions, with LIDAR providing no data in the densest smoke. For the free space state, the fusion method outperformed the LIDAR in smoke conditions by as much as 40% and was typically within 5% of the LIDAR in clear conditions.
机译:开发了一种传感器融合方法,将长波长红外(LWIR)立体视觉与旋转的LIDAR相结合,以改善烟雾遮蔽环境中的测距。该方法可以在清晰和烟雾条件下进行测距,这取决于LIDAR在清晰条件下的高精度以及LWIR摄像机在烟雾中的感知能力。传感器数据在3D多分辨率体素域中使用证据(Dempster-Shafer)理论进行了组合,用于占据和自由空间状态。产生了一种启发式方法,使用返回强度和距离来分离显着衰减和低衰减的LIDAR返回。开发了一种传感器模型以应用来自LIDAR高衰减返回的自由空间状态信息。开发了传感器模型,以应用来自LIDAR低衰减返回和LWIR立体视觉点的已占用和自由空间状态信息。在两种火灾环境中对融合方法进行了评估:具有清晰到浓烟条件的房间走廊场景和舰船火灾场景。通过对照基线测距评估性能来评估室内走廊测试。对于占领状态,融合方法和LIDAR在晴朗的条件下通常在5%到10%的范围内,而融合方法比LIDAR的烟雾条件下的精度通常在5%到10%的范围内,而LIDAR不会提供任何数据。最浓的烟。对于自由空间状态,在烟雾条件下,融合方法的性能优于LIDAR,最高可达40%,在清晰的条件下,融合方法通常仅为LIDAR的5%之内。

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