Multimodal Object Detection and Ranging Based on Camera and Lidar Sensor Fusion for Autonomous Driving

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WEB OF SCIENCE

10
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15

초록

A robust perception system is critical in autonomous driving. It is responsible for object detection, classification, and ranging under challenging circumstances. Camera and lidar sensors provide complementary information, and by combining these two modalities, we can increase the robustness and accuracy of the overall perception system. This paper presents the implementation of sensor fusion based perception using camera images and lidar point clouds for object detection and ranging in a real-time driving environment. The experiment results obtained with our test vehicle demonstrate that the perception of vehicle surroundings can be more effectively achieved by means of camera-lidar sensor fusion compared with using a single type of sensor.

키워드

camera; lidar; sensor fusion; perception; object detection; ranging; autonomous driving
제목
Multimodal Object Detection and Ranging Based on Camera and Lidar Sensor Fusion for Autonomous Driving
저자
Khan, Danish; Baek, Minjin; Kim, Min Young; Han, Dong Seog
DOI
10.1109/APCC55198.2022.9943618
발행일
2022
유형
Proceedings Paper
저널명
2022 27TH ASIA PACIFIC CONFERENCE ON COMMUNICATIONS (APCC 2022): CREATING INNOVATIVE COMMUNICATION TECHNOLOGIES FOR POST-PANDEMIC ERA
페이지
342 ~ 343