Localization in Unstructured Environments: Towards Autonomous Robots in Forests with Delaunay Triangulation
Localization in Unstructured Environments: Towards Autonomous Robots in Forests with Delaunay Triangulation
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DOI：
10.3390/rs12111870
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发表时间：
2020-05
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通讯作者：
Qingqing Li;P. Nevalainen;J. P. Queralta;J. Heikkonen;Tomi Westerlund
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作者：
Qingqing Li;P. Nevalainen;J. P. Queralta;J. Heikkonen;Tomi Westerlund
自主采伐和运输是林业的长期目标。主要挑战之一是森林中车辆和树木的准确定位。森林是非结构化环境，当前基于特征的快速地点识别算法很难找到一组重要的地标。本文提出了一种新颖的方法，其中使用 Delaunay 三角化作为表示格式将局部点云与全局树图进行匹配。我们使用基于拓扑的方法，而不是基于点云的匹配方法。首先，在森林采伐机之前运行时记录树干位置。其次，对所得地图进行 Delaunay 三角化。第三，使用三角形相似性最大化来注册、三角化和匹配自主机器人的局部子图以估计机器人的位置。我们在芬兰列克萨林业站点积累的数据集上测试了我们的方法。带有 3D 激光扫描仪和固定在框架上的地理定位单元的工业收割机记录了总长 200 m 的收割机路径。我们的实验显示 12 厘米标准差。定位精度和实时数据处理速度不超过0.5 m/s。森林作业期间的准确性和速度限制是现实的。
Autonomous harvesting and transportation is a long-term goal of the forest industry. One of the main challenges is the accurate localization of both vehicles and trees in a forest. Forests are unstructured environments where it is difficult to find a group of significant landmarks for current fast feature-based place recognition algorithms. This paper proposes a novel approach where local point clouds are matched to a global tree map using the Delaunay triangularization as the representation format. Instead of point cloud based matching methods, we utilize a topology-based method. First, tree trunk positions are registered at a prior run done by a forest harvester. Second, the resulting map is Delaunay triangularized. Third, a local submap of the autonomous robot is registered, triangularized and matched using triangular similarity maximization to estimate the position of the robot. We test our method on a dataset accumulated from a forestry site at Lieksa, Finland. A total length of 200 m of harvester path was recorded by an industrial harvester with a 3D laser scanner and a geolocation unit fixed to the frame. Our experiments show a 12 cm s.t.d. in the location accuracy and with real-time data processing for speeds not exceeding 0.5 m/s. The accuracy and speed limit are realistic during forest operations.