최소 단어 이상 선택하여야 합니다.
최대 10 단어까지만 선택 가능합니다.
다음과 같은 기능을 한번의 로그인으로 사용 할 수 있습니다.
NTIS 바로가기Journal of advanced computational intelligence and intelligent informatics, v.26 no.2, 2022년, pp.206 - 216
Wang, Qingshan , Zhang, Jun , Liu, Yuansheng , Zhang, Xinchen
LiDAR SLAM technology is an important method for the accurate navigation of automatic vehicles and is a prerequisite for the safe driving of automatic vehicles in the unstructured road environment of complex parks. This paper proposes a LiDAR fast point cloud registration algorithm that can realize ...
10.1016/j.robot.2009.09.009 K. M. Wurm, C. Stachniss, and G. Grisetti, “Bridging the Gap Between Feature- and Grid-based SLAM,” Robotics and Autonomous Systems, Vol.58, No.2, pp. 140-148, 2010.
A. Eliazar and R. Parr, “DP-SLAM: Fast, Robust Simultainous Localization and Mapping Without Predetermined Landmarks,” Proc. of the 18th Int. Joint Conf. on Artificial Intelligence (IJCAI-03), pp. 1135-1142, 2003.
S. Thrun, W. Burgard, and D. Fox, “Probabilistic Robotics,” MIT Press, 2005.
10.1177/0278364911430419 M. Kaess, H. Johannsson, R. Roberts, V. Ila, J. Leonard, and F. Dellaert, “iSAM2: Incremental smoothing and mapping using the bayes tree,” The Int. J. of Robotics Research, Vol.31, pp. 217-236, 2012.
10.1088/1742-6596/1914/1/012019 L. Hengjie, B. Hong, and X. Cheng, “Fast Closed-Loop SLAM based on the fusion of IMU and Lidar,” J. of Physics: Conf. Series, 2021 Int. Conf. on Electrical, Electronics and Computing Technology (EECT 2021), Vol.1914, Article No.012019, 2021.
10.1142/S230138502150014X S. Yuan, H. Wang, and L. Xie, “Survey on Localization Systems and Algorithms for Unmanned Systems,” Unmanned Systems, Vol.9, No.2, pp. 129-163, 2020.
10.1177/1729881421999923 P. Jiang, L. Chen, H. Guo et al., “Novel indoor positioning algorithm based on Lidar/inertial measurement unit integrated system,” Int. J. of Advanced Robotic Systems, Vol.18, No.2, doi: 10.1177/1729881421999923, 2021.
10.1016/j.neucom.2020.06.004 J. Li, X. Zhang, J. Li et al., “Building and optimization of 3D semantic map based on Lidar and camera fusion,” Neurocomputing, Vol.409, pp. 394-407, 2020.
10.20965/jaciii.2018.p0593 X. Guo, Y. Liu, Q. Zhong et al., “Research on Moving Target Tracking Algorithm Based on Lidar and Visual Fusion,” J. Adv. Comput. Intell. Intell. Inform, Vol.22, No.5, pp. 593-601, doi: 10.20965/jaciii.2018.p0593, 2018.
10.20965/jaciii.2018.p0602 Q. Zhong, Y. Liu, X. Guo et al., “Dynamic Obstacle Detection and Tracking Based on 3D Lidar,” J. Adv. Comput. Intell. Intell. Inform, Vol.22, No.5, pp. 602-610, doi: 10.20965/jaciii.2018.p0602, 2018.
10.1002/rob.20103 David Nister, O. Naroditsky, and J. R. Bergen, “Visual odometry for ground vehicle applications,” J. of Field Robotics, Vol.23, No.1, pp. 3-20, 2006.
10.1109/34.121791 P. J. Besl and N. D. McKay, “A Method for Registration of 3D Shapes,” IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol.14, No.2, pp. 239-256, 1992.
S. Rusinkiewicz and M. Levoy, “Efficient Variants of the ICP Algorithm,” Proc. of the 3rd Int. Conf. on 3-D Digital Imaging and Modeling, pp. 145-152, 2001.
10.1016/0262-8856(92)90066-C Y. Chen and G. Medioni, “Object Modelling by Registration of Multiple Range Images,” Image and Vision Computing, Vol.10, No.3, pp. 145-155, 1992.
A. Nuchter, “Parallelization of Scan Matching for Robotic 3D Mapping,” Proc. of the 3rd European Conf. on Mobile Robots, 2007.
10.1007/978-3-642-04667-4_20 D. Qiu, S. May, and A. Nuchter, “GPU-Accelerated Nearest Neighbor Search for 3D Registration,” Proc. of the Int. Conf. on Computer Vision Systems, pp. 194-203, 2009.
P. Biber and W. Strasser, “The Normal Distributions Transform: A New Approach to Laser Scan Matching,” Proc. 2003 IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS 2003), 2003.
10.1002/rob.20204 M. Magnusson, A. Lilienthal, and T. Duckett, “Scan registration for autonomous mining vehicles using 3D-NDT,” J. of Field Robotics, Vol.24, No.10, pp. 803-827, 2007.
10.1016/j.robot.2009.07.009 M. Bosse and R. Zlot, “Keypoint Design and Evaluation for Place Recognition in 2D Lidar Maps,” Robotics and Autonomous Systems, Vol.57, No.12, pp. 1211-1224, 2009.
10.1007/s10514-016-9548-2 J. Zhang and S. Singh, “Low-drift and Real-time Lidar Odometry and Mapping,” Autonomous Robots, Vol.41, No.2, pp. 401-416, 2017.
D. Zhu, “Point Cloud Library PCL Learning Course,” Beijing Aerospace University Press, 2012.
M. Quigley, B. Gerkey, K. Conley et al., “ROS: An open-source robot operating system,” Workshop on Open Source Software (Collocated with ICRA 2009), 2009.
*원문 PDF 파일 및 링크정보가 존재하지 않을 경우 KISTI DDS 시스템에서 제공하는 원문복사서비스를 사용할 수 있습니다.
오픈액세스 학술지에 출판된 논문
※ AI-Helper는 부적절한 답변을 할 수 있습니다.