户外环境下四足机器人的扫描匹配方法

Yanli Li, Long Cui, R. Song, Chenglin Pang, Yibin Li
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引用次数: 0

摘要

在室外非结构化环境下,由于四足机器人的动态运动,激光连续扫描的相对位移和旋转角度较大。目前广泛使用的扫描匹配方法ICP如果没有良好的初始值,容易收敛到局部最优。本文提出了一种基于快速鲁棒点云分割的改进Super 4PCS方法。通过点云分割预处理,去除植被、树叶等不稳定障碍物,只提取特征明显的大型目标点云。为Super 4PCS配准算法提供更高效的待配准点云。实验证明,改进的方法可以应用于户外非结构化环境下的四足机器人,加快了匹配速度,提高了点云配准的精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Scan Matching Method For Quadruped Robots In Outdoor Environment
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.
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