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Fast and efficient traversable region extraction using quantized elevation map and 2D laser rangefinder

机译:使用量化高程图和2D激光测距仪快速高效地遍历区域

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In this paper, we propose a fast and efficient traversable region extraction using quantized digital elevation map (Q-DEM) from the data obtained by the 2D laser rangefinder at indoor-outdoor environments. Generally, the structure of tilting a 2D laser rangefinder is a widespread strategy to acquire precise 3D point clouds. But in this research, using low-cost microcontroller-based modularization and improved tilting mechanism which controls the tilting motion for each of the scanning areas, we can not only obtain reliable and dense 3D point clouds with relative uniform distribution from single laser scans, but also enhance the accuracy of sensor measurements. Furthermore for fast computation and efficient management of the raw 3D data acquisition, we firstly adopt the modified voxel grid filtering with adaptive sampling of scalar distance fields, and then generate a grayscale reconstruction based quantized elevation map by applying a non-linear measurement model for extracted data sets. Especially through the proposed quantized elevation map representation, we have a relatively simple and fast data processing operation by leveraging the advantages of existing image processing techniques. Finally, for the implementation of the stable traversable region extraction, we mainly divided into two main categories, "traversable" and "non-traversable regions" with histogram and edge/texture information of Q-DEM, and then more detailed distinction for terrain classification (flat region, slope, stair, and obstacle) is performed according to the characteristics of each terrain. The experimental results show that our proposed method has a stable terrain classification performance(Avg. 83%) based on the fast map generation(Avg. 10ms) with an effective mapping capability, regardless of the variety of environmental characteristics. As a result, our proposed method was able to make a more stable path generation and utilization for mapping and navigation in given environment.
机译:在本文中,我们提出了一种利用量化数字高程图(Q-DEM)从室内外环境下的2D激光测距仪获得的数据中快速,有效地遍历区域的方法。通常,倾斜2D激光测距仪的结构是获取精确3D点云的广泛策略。但是在这项研究中,使用低成本的基于微控制器的模块化和改进的倾斜机制来控制每个扫描区域的倾斜运动,我们不仅可以从单个激光扫描中获得相对均匀分布的可靠且密集的3D点云,而且还可以提高传感器测量的准确性。此外,为快速计算和有效管理原始3D数据采集,我们首先采用对标量距离场进行自适应采样的改进体素网格滤波,然后通过应用非线性测量模型来提取基于灰度重构的量化高程图数据集。尤其是通过提出的量化高程图表示,我们可以利用现有图像处理技术的优势,进行相对简单且快速的数据处理。最后,为了实现稳定的可穿越区域提取,我们主要通过Q-DEM的直方图和边缘/纹理信息将主要分为“可穿越区域”和“不可穿越区域”两大类,然后对地形分类进行更详细的区分(平坦区域,坡度,楼梯和障碍物)根据每个地形的特性执行。实验结果表明,无论环境特征如何变化,基于快速的地图生成(平均10ms)和有效的制图能力,本文提出的方法具有稳定的地形分类性能(平均83%)。结果,我们提出的方法能够在给定的环境中为映射和导航提供更稳定的路径生成和利用。

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