Earticle

초록

영어

In the present scenario, the self-driving industry is in the commercialization stage of the consumer market. There are no longer any difficulties simply detecting an object and performing certain tasks in terms of vehicle control and navigation. Nevertheless, unexpected problems arise due to occlusion, unbalanced ground, and bad weather. This paper presents a method for correcting inaccurate distance recognition results when a vehicle vibrates against the unbalanced ground. The proposed method follows a pipeline of preprocessing techniques such as LiDAR-camera calibration, 3D point cloud data acquisition from LiDAR and camera to model 3D plane equations in RANSAC. The distance error is corrected by estimating the orientations from an IMU sensor in real-time and by assessing Rotation and translation in accordance with the pose changes of the vehicle.

목차

Abstract
I. INTRODUCTION
II. METHOD
A. Estimating Distance using LiDAR-Camera calibration
B. Prediction of the distance using car-pose simulation
III. EXPERIMENTS
IV. CONCLUSION
ACKNOWLEDGMENT
REFERENCES

키워드

저자

• Dong-Hyun Lee [ Dept. of Electrical and Computer Engineering Inha University ]
• Sun-Won Hong [ Department of Electrical and Computer Engineering Inha University ]
• Hyung-Jin Han [ Department of Electrical and Computer Engineering Inha University ]
• Xing-You Li [ Department of Electrical and Computer Engineering Inha University ]
• Jong-Kwang Kim [ Department of Electrical and Computer Engineering Inha University ]
• Hakil Kim [ Department of Electrical and Computer Engineering Inha University ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  한국차세대컴퓨팅학회 학술대회

• 간기

  반년간

• 수록기간

  2021~2025

• 십진분류

  KDC 566 DDC 004