Distortion correction of 3D laser sensor measurements caused by mobile robot motion

Abstract

U diplomskom radu opisana je implementacija regresije Gaussovih procesa za estimiranje stanje u kontinuiranom vremenu. Estimacija gibanja mobilnog robota je simulirana i korištena za korekciju distorzije rotirajućeg 3D laserskog senzora. Teoretski zasnovan algoritam je razmotren. Korištenjem ROS-a za snimanje senzorskih mjerenja i algoritma zasnovanog na ICP estimaciji vlastitog gibanja u C/C++, dobiveno je okružje za provjeru algoritma. Poboljšanje ICP algoritma pri pravocrtnom gibanju uz smanjenje pogreške u odnosu na smjerove okomite na smjer gibanja, predstavlja korisne rezultate.This thesis describes an implementation of Gaussian process regression for continuous time state estimation. The estimation of mobile robot motion has been simulated and used as a tool in correcting the distorsion of the rotating 3D laser sensor. A theoretically established algorithm is preseted and discussed. Using ROS for sensor data acquisition and the ICP based robot ego motion algorithm in C/C++, we get a real-world setup for algorithm validation. Improving the ICPs performance on straight line experiments by decreasing error in directions perpendicular to the motion, is valuable results that emerge

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This paper was published in Croatian Digital Thesis Repository.

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