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The U.S. Army is actively pursuing 3D active imaging techniques using laser sources emitting at 1.5 μm. This eyesafe short wave infrared (SWIR) waveband is advantageous due to both the improved eye safety and atmospheric propagation through obscurants. NVESD has several active programs in this area, which will be reviewed in this paper. These are: 1) single-pixel scanned imaging laser radar, 2) 2D gated SWIR imaging, and 3) 3D-flash laser radar. These systems are being evaluated for various targeting scenarios, including as potential payloads on unmanned air-vehicles, ground vehicles and other sensor suites. Applications include low-cost long-range target identification, identification of heavily obscured targets, obstacle avoidance, and high resolution imaging.

In this paper, an analysis of the precision of range sensors is presented. Light Detection and Ranging (LIDAR) data from three different sensors (HLS-LFCD-LDS, SICK TIM561, and Kinect V2), stereo data from the Realsense D435, and structured light data from both Kinect V1 for Xbox and the Xtion PRO Live were analyzed regarding the influence of range, incident angle to the surface, and surface material. In addition, a comparison with standard deviation models based on vendor-provided specifications was performed. We found that the vendor specifications are in general not specific enough to facilitate accurate sensor simulations. Therefore, we developed a data-driven model for range precision. Our model can be used to create realistic sensor simulations and to develop robot navigation algorithms weighing sensor range readings based on the precision.

The U.S. Army is actively pursuing 3D active imaging techniques using laser sources emitting at 1.5 μm. This eyesafe short wave infrared (SWIR) waveband is advantageous due to both the improved eye safety and atmospheric propagation through obscurants. NVESD has several active programs in this area, which will be reviewed in this paper. These are: 1) single-pixel scanned imaging laser radar, 2) 2D gated SWIR imaging, and 3) 3D-flash laser radar. These systems are being evaluated for various targeting scenarios, including as potential payloads on unmanned air-vehicles, ground vehicles and other sensor suites. Applications include low-cost long-range target identification, identification of heavily obscured targets, obstacle avoidance, and high resolution imaging.

Since there is no prior global map of the environment when autonomic operating in the unknown indoor environment, the mobile robot can’t achieve locating by matching the part map and the prior global map. Furthermore, there would be accumulated measurement error when using a single sensor, which would lead to the failure of locating. In order to solve the problem about the location of the robot in the unknown environment and improve the location precision, this paper proposes a new locating method based on the laser radar. The method makes full use of the environment information acquired by the laser radar to obtain a coarse matching location result for reference, then combines an improved ICP algorithm to get the precision matching location result, finally the result is used to achieve the precise locating of the robot.