Detail publikace

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

JELÍNEK, A.

Originální název

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

Anglický název

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

Jazyk

en

Originální abstrakt

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.

Anglický abstrakt

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.

Dokumenty

BibTex


@inproceedings{BUT114309,
  author="Aleš {Jelínek}",
  title="Practical Aspects of Total Least Squares Vectorization of Point Clouds in Mobile Robotics",
  annote="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.",
  booktitle="IFAC Conference on Programmable Devices and Embedded Systems",
  chapter="114309",
  doi="10.1016/j.ifacol.2015.07.031",
  howpublished="online",
  number="2015",
  year="2015",
  month="may",
  pages="193--198",
  type="conference paper"
}