Open Access
MATEC Web Conf.
Volume 160, 2018
International Conference on Electrical Engineering, Control and Robotics (EECR 2018)
Article Number 06005
Number of page(s) 6
Section Intelligent Robot Design and Control
Published online 09 April 2018
  1. R Smith, M self, P Cheesseman. Estimating uncertain spatial relationships in robotics [A]. Proc of Conf Uncertainty in Artificial Intelligence[C]. Amsterdam: North-Holland, 1988, 435-461. [CrossRef] [Google Scholar]
  2. Taizhi Lv. A new anti-disturbance EKF-SLAM algorithm [J]. computer engineering, 2012, 38(21):1-4. [Google Scholar]
  3. Haiqiang Zhang, Lihua Dou, Hao Fang, etc. An improved SLAM algorithm based on compression type EKF [J]. System Simulation, 2009, 21(18):5668-5680. [Google Scholar]
  4. Wu Zhou, Chunxia Zhao, Yaqiang Shen, etc. The study of SLAM based on global observation map model [J]. Robot, 2010, 32(5):647-654. [Google Scholar]
  5. S J Julier, J K Uhlmann. H Durrant-Whyte. A New Method for the Nonlinear Transformation of Means and Covariances in Filters and Estimation [J]. IEEE Transactions on Automatic Control (S0018-9286), 2000, 45(3):477-482. [Google Scholar]
  6. Xinxi Shi, Chunxia Zhao, Jianhui Guo. SLAM framework algorithm of mobile robot based on PF / EKF UKF [J]. Digital Journal. 2009, 8:1865-1868. [Google Scholar]
  7. Merwe R V D, Wan E A, The Squre-Root Unscented Kalman Filter for State and Parameter–Estimation[C].International Conference on Acoustics, Speech, and Signal Processing, Utah,2001. [Google Scholar]
  8. Jing Yang, Nanning Zheng. A GPS/DR Integrated Positioning Algorithm Based on SR-UKF. System Simulation [J].2009, 21(3):721-722,742. [Google Scholar]
  9. Lei An, Guoliang Zhang, Wenjun Tan. The Indoor Kalman filter localization algorithm of Robot based on RSSI [J]. Computer Engineering and Application. 2010, 48(8):230-232. [Google Scholar]
  10. Shurong Li, Pengfei Ni. SLAM algorithm based on the square root of UKF [J]. Computer Engineering and Application, 2011, 47(22):209-212. [Google Scholar]
  11. S J Julier, J K Uhlmann. Reduced sigma point filters for propagation of means and covariances through nonlinear transformation: Proc. of American Control Conf[C]. Jefferson City, 2002: 887-892. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.