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A Scan Matching Method For Quadruped Robots In Outdoor Environment

机译:户外环境中四足机器人的扫描匹配方法

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In the outdoor unstructured environment, the relative displacement and rotation angle of the continuous laser scans are large due to the dynamic motion of the quadruped robots. Without good initial value, widely-used scan matching method ICP is prone to converge to a local optimum. In this paper, an improved Super 4PCS method based on fast and robust point cloud segmentation is proposed. Through point cloud segmentation preprocessing, unstable obstacles such as vegetation and leaves are removed and only large object point clouds with obvious features are extracted. More efficient point clouds to be registered are provided to Super 4PCS registration algorithm. Experiments prove that the improved method can be applied to quadruped robots in outdoor unstructured environment, speed up the matching and improve the accuracy of point cloud registration.
机译:在室外非结构化环境中,由于四足机器人的动态运动,连续激光扫描的相对位移和旋转角度大。 如果没有良好的初始值,则广泛使用的扫描匹配方法ICP容易收敛到本地最佳。 本文提出了一种基于快速和鲁棒点云分割的改进的超级4PCS方法。 通过点云分割预处理,除去植被和叶子等不稳定障碍物,并且仅提取具有明显特征的大物体点云。 更高效的点云被提供给超级4PCS注册算法。 实验证明,改进的方法可以应用于户外非结构化环境中的四足机器人,加快匹配并提高点云登记的准确性。

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