Simultaneous Localization and Mapping of Mobile Robot with Research and Implementation
Chen Du, Yu Du
Available Online April 2019.
- https://doi.org/10.2991/icmeit-19.2019.92How to use a DOI?
- Sensor technique; Simultaneous localization and mapping; Rao-Blackwellized particle filter; Robot operating system.
- In the process of autonomous navigation, mobile robots need to build maps of the surrounding environment and simultaneous localization. The Rao-Blackwellzed particle filter algorithm is one of the methods to efficiently solve the problem that simultaneous localization and mapping of mobile robots. At present, Mapping of inconsistent have long been the focus of research. In order to solve this problem, this paper provides an algorithm which uses high-precision Laser data to correct the proposed distribution based on odometer readings, focus sampling on the possible areas of observation information, reduces the error of proposed distribution, and establish a more accurate map environment. Finally, the experimental verification was carried out on the Bulldog mobile robot platform equipped with a 16-line Laser sensor. The results show that the optimized method of performance is more stable, can improves the diversity of particles and creates high-precision environmental maps online in real time.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Chen Du AU - Yu Du PY - 2019/04 DA - 2019/04 TI - Simultaneous Localization and Mapping of Mobile Robot with Research and Implementation PB - Atlantis Press SP - 577 EP - 580 SN - 2352-538X UR - https://doi.org/10.2991/icmeit-19.2019.92 DO - https://doi.org/10.2991/icmeit-19.2019.92 ID - Du2019/04 ER -