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      KCI등재 SCOPUS

      외부 시스템을 이용한 Monocular camera-3D LiDAR융합 시스템의 Non-overlapping 외부 교정 방법에 대한 연구 = A Study on the Non-overlapping Extrinsic Calibration Method of a Monocular camera-3D LiDAR Fusion System Using an External System

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      https://www.riss.kr/link?id=A108367770

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      다국어 초록 (Multilingual Abstract)

      This study presents a novel framework for the extrinsic calibration of mono camera and LiDAR with a non-overlapping field of view. The conventional non-overlapping extrinsic calibration utilizes a motion-based calibration method. However, motionbased ...

      This study presents a novel framework for the extrinsic calibration of mono camera and LiDAR with a non-overlapping field of view. The conventional non-overlapping extrinsic calibration utilizes a motion-based calibration method. However, motionbased calibration has a disadvantage in that the vehicle must be moving. In order to solve extrinsic calibration problems under such constraint configurations, the proposed solution uses external sensors that are located away from vehicle. First, the external camera and vehicle camera utilize an aruco marker. Second, the external LiDAR and vehicle LiDAR utilize a scan matching method. In this study, a Gazebo simulator was utilized to show the accuracy of the proposed method. The external LiDAR used Velodyne HDL 64ch, the vehicle LiDAR used Puck 16ch, and the camera used the Blackfly color sensor from FLIR.

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      다국어 초록 (Multilingual Abstract)

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      참고문헌 (Reference) 논문관계도

      1 장경석 ; 하종은, "칼라 체스보드를 이용한 RGB-D 센서와 로봇의 외부보정" 제어·로봇·시스템학회 25 (25): 63-68, 2019

      2 이동근 ; 함준혁 ; 한재윤 ; 임경일, "도심 환경속 판단 보조를 위한 교통섬 지형분할 및 객체분류" 제어·로봇·시스템학회 27 (27): 801-808, 2021

      3 J. Jeong, "The road is enough! Extrinsic calibration of non-overlapping stereo camera and LiDAR using road information" 4 (4): 2831-2838, 2019

      4 D. J. Yeong, "Sensor and sensor fusion technology in autonomous vehicles: A review" 21 (21): 2140-, 2021

      5 S. Kim, "Semantic point cloud-based adaptive multiple object detection and tracking for autonomous vehicles" 38 (38): 1856-1874, 2022

      6 Z. Taylor, "Motion-based calibration of multimodal sensor arryas" 4843-4850, 2015

      7 A. Dhall, "LiDAR-camera calibration using 3D-3D point correspondences"

      8 Y. Na, "Interaction-aware Trajectory Prediction of Surrounding Vehicles based on Hierarchical Framework in Highway Scenarios" 1060-1065, 2022

      9 R. Horaud, "Hand-eye calibration" 14 (14): 195-210, 1995

      10 A. Segal, "Generalized-icp" 2 (2): 435-, 2009

      1 장경석 ; 하종은, "칼라 체스보드를 이용한 RGB-D 센서와 로봇의 외부보정" 제어·로봇·시스템학회 25 (25): 63-68, 2019

      2 이동근 ; 함준혁 ; 한재윤 ; 임경일, "도심 환경속 판단 보조를 위한 교통섬 지형분할 및 객체분류" 제어·로봇·시스템학회 27 (27): 801-808, 2021

      3 J. Jeong, "The road is enough! Extrinsic calibration of non-overlapping stereo camera and LiDAR using road information" 4 (4): 2831-2838, 2019

      4 D. J. Yeong, "Sensor and sensor fusion technology in autonomous vehicles: A review" 21 (21): 2140-, 2021

      5 S. Kim, "Semantic point cloud-based adaptive multiple object detection and tracking for autonomous vehicles" 38 (38): 1856-1874, 2022

      6 Z. Taylor, "Motion-based calibration of multimodal sensor arryas" 4843-4850, 2015

      7 A. Dhall, "LiDAR-camera calibration using 3D-3D point correspondences"

      8 Y. Na, "Interaction-aware Trajectory Prediction of Surrounding Vehicles based on Hierarchical Framework in Highway Scenarios" 1060-1065, 2022

      9 R. Horaud, "Hand-eye calibration" 14 (14): 195-210, 1995

      10 A. Segal, "Generalized-icp" 2 (2): 435-, 2009

      11 A. J. Sathyamoorthy, "Densecavoid: Real-time navigation in dense crowds using anticipatory behaviors" 11345-11352, 2020

      12 H. Men, "Color point cloud registration with 4D ICP algorithm" 1511-1516, 2011

      13 J. Beltrán, "Automatic extrinsic calibration method for lidar and camera sensor setups" 2022

      14 S. Kuutti, "A survey of state-of-the-art localization techniques and their potentials for autonomous vehicle applications" 5 (5): 829-846, 2018

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