Research on the Algorithm of Simulation Location and Mapping of Mobile Robot
Authors
Qunying Chen
Corresponding Author
Qunying Chen
Available Online April 2017.
- DOI
- 10.2991/fmsmt-17.2017.31How to use a DOI?
- Keywords
- Mobile robot, Simulation location and mapping, autonomous navigation
- Abstract
The simultaneous localization and mapping (SLAM) of mobile robot is the basic problem and hot spot in the field of robotics, and is also the key to realize autonomous navigation and control decision. This paper first introduces the source of the SLAM problem, and gives different solutions of the problem, including Kalman Filter method, Extended Kalman Filter method and Particle Filter method. The advantages and disadvantages of the three methods are discussed in the paper. Finally, this paper points out the research directions of SLAM problem to provide some reference for the relative researchers.
- Copyright
- © 2017, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Qunying Chen PY - 2017/04 DA - 2017/04 TI - Research on the Algorithm of Simulation Location and Mapping of Mobile Robot BT - Proceedings of the 2017 5th International Conference on Frontiers of Manufacturing Science and Measuring Technology (FMSMT 2017) PB - Atlantis Press SP - 150 EP - 154 SN - 2352-5401 UR - https://doi.org/10.2991/fmsmt-17.2017.31 DO - 10.2991/fmsmt-17.2017.31 ID - Chen2017/04 ER -