Proceedings of the 2017 5th International Conference on Frontiers of Manufacturing Science and Measuring Technology (FMSMT 2017)

Research on the Algorithm of Simulation Location and Mapping of Mobile Robot

Authors
Qunying Chen
Corresponding Author
Qunying Chen
Available Online April 2017.
DOI
https://doi.org/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.
Open Access
This is an open access article distributed under the CC BY-NC license.

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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  - https://doi.org/10.2991/fmsmt-17.2017.31
ID  - Chen2017/04
ER  -