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Practical Aspects of Total Least Squares Vectorization of Point Clouds in Mobile Robotics

机译:移动机器人中点云总最小二乘矢量化的实际方面

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摘要

Fast and reliable point cloud processing is a challenging task, especially when online running of the implementation on a mobile robot is required. This paper summarizes generally usable optimization techniques (hardware dependent implementation details are not covered) for vectorization of the point cloud using the least squares approach. Formulas for efficient implementation, methodology of tuning of the control variables, posprocessing for result reliability, as well as illustrative examples are all covered in the text. The discussed suggestions were experimentally proofed to give increased performance (in terms of speed and quality of approximation) with respect to basic implementation.
机译:快速可靠的点云处理是一项具有挑战性的任务,尤其是当需要在移动机器人上在线运行实施时。本文总结了使用最小二乘法对点云进行矢量化的一般可用的优化技术(不涉及硬件相关的实现细节)。文中涵盖了有效实现的公式、控制变量的调整方法、结果可靠性的处理以及说明性示例。所讨论的建议经过实验验证,在基本实现方面具有更高的性能(在速度和近似质量方面)。

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