自主挖掘机地形可穿越性测绘与导航系统

Tianrui Guan, Zhenpeng He, Ruitao Song, Dinesh Manocha, Liangjun Zhang
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引用次数: 17

摘要

我们提出了一种地形可穿越性测绘和导航系统(TNS),用于非结构化环境下的自主挖掘机应用。我们使用一种有效的方法从RGB图像和3D点云中提取地形特征,并将其合并到全球地图中用于规划和导航。该系统能够适应不断变化的环境,实时更新地形信息。此外,我们提出了一个新的数据集,即复杂工地地形(CWT)数据集,该数据集由来自建筑工地的RGB图像组成,根据可导航性分为七个类别。与以往的SOTA方法相比,我们的算法将映射精度提高了4.17-30.48%,将可遍历性图的MSE降低了13.8-71.4%。我们将测绘方法与自主挖掘机导航系统中的规划和控制模块相结合,整体成功率提高了49.3%。基于TNS,我们展示了第一台可以在由深坑、陡坡、岩桩和其他复杂地形特征组成的非结构化环境中导航的自主挖掘机。
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TNS: Terrain Traversability Mapping and Navigation System for Autonomous Excavators
We present a terrain traversability mapping and navigation system (TNS) for autonomous excavator applications in an unstructured environment. We use an efficient approach to extract terrain features from RGB images and 3D point clouds and incorporate them into a global map for planning and navigation. Our system can adapt to changing environments and update the terrain information in real-time. Moreover, we present a novel dataset, the Complex Worksite Terrain (CWT) dataset, which consists of RGB images from construction sites with seven categories based on navigability. Our novel algorithms improve the mapping accuracy over previous SOTA methods by 4.17-30.48% and reduce MSE on the traversability map by 13.8-71.4%. We have combined our mapping approach with planning and control modules in an autonomous excavator navigation system and observe 49.3% improvement in the overall success rate. Based on TNS, we demonstrate the first autonomous excavator that can navigate through unstructured environments consisting of deep pits, steep hills, rock piles, and other complex terrain features.
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