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Stereovision-based lateral offset measurement for vehicle navigation in cultivated stubble fields

机译:基于立体视觉的侧向偏移量测量,用于耕地留茬场中的车辆导航

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摘要

In auto-guidance of agricultural vehicles in cultivated stubble fields, a precise measurement of the vehicle's lateral offset could help achieve improved navigation accuracy. This paper presents an automated method for measuring a vehicle's lateral offset for such an application. The basic concept was to use static ground features as references to detect the vehicle's lateral offset. A stereo image-processing algorithm was developed which detected and tracked ground features captured in two consecutive field images, acquired using a vehicle-mounted stereo camera. These ground features were used as reference points to calculate the lateral offset. Field validation tests showed that this algorithm could provide accurate relative lateral offset measurements. Over a 10 m straight path, the deviation of measurements from ground truth was less than 50 mm. As this method was designed to measure relative offset, the field tests also revealed that it needed a realignment of the installation pose of the camera and the desired heading direction of the vehicle after a turn to ensure the measurement deviation less than 50 mm. Although the realignment algorithm was outside the scope of this research, the results proved the possibility of using an imaging sensor for the detection of the lateral offset of a vehicle to guide agricultural vehicles automatically in cultivated stubble fields without obvious referencing landmarks
机译:在耕作茬地的农用车辆自动引导中,精确测量车辆的侧向偏移量可以帮助提高导航精度。本文提出了一种用于这种应用的自动测量车辆横向偏移的方法。基本概念是使用静态地面特征作为检测车辆横向偏移的参考。开发了一种立体图像处理算法,该算法可以检测并跟踪在使用车载立体摄像机获取的两个连续场图像中捕获的地面特征。这些地面特征被用作计算横向偏移的参考点。现场验证测试表明,该算法可以提供准确的相对横向偏移测量。在10 m的直线路径上,测量值与地面真实情况的偏差小于50 mm。由于此方法旨在测量相对偏移,因此现场测试还表明,在转弯后需要重新设置摄像机的安装姿态和所需的车辆前进方向,以确保测量偏差小于50 mm。尽管重新对准算法不在本研究的范围之内,但结果证明了使用成像传感器检测车辆的横向偏移的可能性,从而可以在耕作的残茬田地中自动引导农用车辆而无需明显参考地标

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