Paper Title
Basic Experiment of Lidar Sensor Measurement Directional Instability For Moving and Vibrating Object

Abstract
The purpose of this paper is to develop a new scan matching method for LiDAR SLAM. One of the problems in scan matching is that as the amount of data increases, the computation time becomes enormous. Automated driving uses large amounts of data for safety reasons, but this requires a high-performance PC in the vehicle. We therefore devised a method that allows estimation with a smaller number of data while keeping safety. It is the Virtual LRF and the two-sided search method. Virtual LRF is a method to extract only important data from map data by reproducing LRF on a PC. The two-tailed search method is a method that aims to improve the accuracy of estimation by efficiently using data not considered in the estimation by the ICP algorithm. New map data is generated in the Virtual LRF, and the matching process is performed using the two-sided search method. In the experiment, we simulated the rotational motion of the target object on a PC. We estimated each using the ICP and two-tailed search method, and compared the effects on the estimation with and without the Virtual LRF. The graphs of the evaluation function E (Fig. 6(b), 6(d), 7(b), and 7(d)) show that we succeeded in reducing the local minimums, which is a major obstacle to estimation, three out of four times in this experiment In addition, there are fewer cases of extremely small estimable areas when the map is changed than before. In the future, we will analyze the effects of the LRF in the case of parallel shifts, and seek more effective ways to use the virtual LRF. Keywords - ICP, LIDAR, Selfpositionestimation

Author - Toshiki Asano, Hideki Toda

Published : Volume-10,Issue-11  ( Nov, 2023 )

	|		PDF	|	Viewed - 11	|	Published on 2024-01-24