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Journal of Robotics
Volume 2011, Article ID 257852, 12 pages
http://dx.doi.org/10.1155/2011/257852
Research Article

A Light-and-Fast SLAM Algorithm for Robots in Indoor Environments Using Line Segment Map

1Department of Electrical Engineering, National Tsing-Hua University 101, Section 2, Kuang-Fu Road, Hsinchu 30013, Taiwan
2Department of Electrical Engineering, National Tsing-Hua University 720R, EECS Bldg, 101, Section 2, Kuang-Fu Road, Hsinchu 30013, Taiwan
3Department of Electrical Engineering, National Tsing-Hua University 818, EECS Bldg, 101, Section 2, Kuang-Fu Road, Hsinchu 30013, Taiwan

Received 19 January 2011; Accepted 15 March 2011

Academic Editor: Heinz Wörn

Copyright © 2011 Bor-Woei Kuo et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [12 citations]

The following is the list of published articles that have cited the current article.

  • Chuan-Han Cheng, Chih-Yen Chen, Jie-Jhong Liang, Ting-Nan Tsai, Chih-Yin Liu, and Tzuu-Hseng S. Li, “Design and implementation of prototype service robot for shopping in a supermarket,” 2017 International Conference on Advanced Robotics and Intelligent Systems (ARIS), pp. 46–51, . View at Publisher · View at Google Scholar
  • Joao Rodrigues, Carlos Cardeira, Fernando Carreira, Joao M. F. Calado, and Paulo Oliveira, “A Bayesian grid method PCA-based for mobile robots localization in unstructured environments,” 2013 16th International Conference on Advanced Robotics (ICAR), pp. 1–6, . View at Publisher · View at Google Scholar
  • Guo-Shing Huang, and Shun-Yu Pan, “Map construction and exploration with measurements of laser rangefinders,” 2017 IEEE International Conference on Mechatronics and Automation (ICMA), pp. 1665–1669, . View at Publisher · View at Google Scholar
  • Fernando Carreira, Joao M. F. Calado, Carlos Cardeira, and Paulo Oliveira, “Enhanced PCA-based localization using depth maps with missing data,” 2013 13th International Conference on Autonomous Robot Systems, pp. 1–8, . View at Publisher · View at Google Scholar
  • Yassin Abdelrasoul, Abu Bakar Sayuti HM Saman, and Patrick Sebastian, “A quantitative study of tuning ROS gmapping parameters and their effect on performing indoor 2D SLAM,” 2016 2nd IEEE International Symposium on Robotics and Manufacturing Automation (ROMA), pp. 1–6, . View at Publisher · View at Google Scholar
  • Han-Gyeol Kim, Jeong-Yean Yang, and Dong-Soo Kwon, “Experience based domestic environment and user adaptive cleaning algorithm of a robot cleaner,” 2014 11th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI), pp. 176–178, . View at Publisher · View at Google Scholar
  • Shang-Yen Lin, and Yung-Chang Chen, “SLAM and Navigation in Indoor Environments,” Advances in Image and Video Technology, vol. 7087, pp. 48–60, 2011. View at Publisher · View at Google Scholar
  • Shuai Guo, Shu-Gen Ma, Bin Li, Ming-Hui Wang, and Yue-Chao Wang, “A Data Association Approach Based on Multi-rules in VorSLAM,” Acta Automatica Sinica, vol. 39, no. 6, pp. 883–894, 2013. View at Publisher · View at Google Scholar
  • Jacky Chow, Derek Lichti, Jeroen Hol, Giovanni Bellusci, and Henk Luinge, “IMU and Multiple RGB-D Camera Fusion for Assisting Indoor Stop-and-Go 3D Terrestrial Laser Scanning,” Robotics, vol. 3, no. 3, pp. 247–280, 2014. View at Publisher · View at Google Scholar
  • Fernando Carreira, Joao M. F. Calado, Carlos Cardeira, and Paulo Oliveira, “Enhanced PCA-Based Localization Using Depth Maps with Missing Data,” Journal Of Intelligent & Robotic Systems, vol. 77, no. 2, pp. 341–360, 2015. View at Publisher · View at Google Scholar
  • Jaehoon Jung, Sanghyun Yoon, Sungha Ju, and Joon Heo, “Development of Kinematic 3D Laser Scanning System for Indoor Mapping and As-Built BIM Using Constrained SLAM,” Sensors, vol. 15, no. 10, pp. 26430–26456, 2015. View at Publisher · View at Google Scholar
  • Marc J. Gallant, and Joshua A. Marshall, “The LiDAR compass: Extremely lightweight heading estimation with axis maps,” Robotics and Autonomous Systems, 2016. View at Publisher · View at Google Scholar