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A New Image Stabilization Model for Vehicle Navigation

机译:一种新的车辆导航图像稳定模型

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When a video camera is mounted on a vehicle’s frame, it experiences the same ride as a passenger and is subject to vertical displacement as the vehicle hits bumps on the road. This results in a captured video that may be difficult to watch because the bumps are transferred to the recorded video. This paper presents a new image stabilization model for vehicle navigation that can remove the effect of vertical vehicular motion due to road bumps. It uses a wheel sensor that monitors the wheel’s reaction with respect to road disturbances prior to the vehicle’s suspension system. This model employs an inexpensive sensor and control circuitry. The vehicle’s suspension system, bumpy road, and the compensation control system are modeled analytically. Experimental results show that the proposed model works suc-cessfully. It can eliminate 10 cm of drift and results in only 1 cm disturbance at the onset and the end of bumps.
机译:当摄像机安装在车架上时,它会遇到与乘客相同的乘坐过程,并且会在车辆撞到道路颠簸时发生垂直位移。这导致捕获的视频可能难以观看,因为颠簸转移到了录制的视频上。本文提出了一种用于车辆导航的新图像稳定模型,该模型可以消除由于道路颠簸而引起的垂直车辆运动的影响。它使用车轮传感器,该车轮传感器在车辆悬架系统之前监视车轮对道路干扰的反应。该模型采用便宜的传感器和控制电路。车辆的悬架系统,崎road不平的道路和补偿控制系统均经过分析建模。实验结果表明,所提出的模型是成功的。它可以消除10 cm的漂移,并且在碰撞的开始和结束时仅造成1 cm的干扰。

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