首页> 外文会议>IEEE/RSJ International Conference on Intelligent Robots and Systems;IROS 2012 >Real-time velocity estimation based on optical flow and disparity matching
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Real-time velocity estimation based on optical flow and disparity matching

机译:基于光流和视差匹配的实时速度估计

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A high update rate of metric velocity values is crucial for a robust operation of navigation control loops of mobile robots such as micro aerial vehicles (MAVs). An efficient way for obtaining metric velocity of robots without external reference are image-based optical flow measurements, scaled with the distance between camera and the observed scene. However, since optical flow and stereo vision are computationally intensive tasks, metric optical flow calculations on embedded systems are typically only possible at limited frame rate. In this work, we therefore present an FPGA-based platform with the capability of calculating real-time metric optical flow at 127 frames per second and 376×240 resolution. Radial undistortion, image rectification, disparity estimation and optical flow calculation tasks are performed on a single FPGA without the need for external memory. The platform is perfectly suited for mobile robots or MAVs due to its low weight and low power consumption.
机译:公制速度值的高更新率对于诸如微型飞行器(MAV)之类的移动机器人的导航控制环的稳健运行至关重要。在没有外部参考的情况下获取机器人度量速度的有效方法是基于图像的光流测量,该测量随相机和观察到的场景之间的距离缩放。但是,由于光流和立体视觉是计算量很大的任务,因此通常只能在有限的帧速率下对嵌入式系统进行度量光流计算。因此,在这项工作中,我们提出了一个基于FPGA的平台,该平台能够以每秒127帧和376×240的分辨率计算实时度量光流。径向不失真,图像校正,视差估计和光流计算任务在单个FPGA上执行,而无需外部存储器。该平台重量轻,功耗低,非常适合移动机器人或MAV。

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