Title
A SLAM with simultaneous construction of 2D and 3D maps based on Rao-Blackwellized particle filters
Abstract
This paper presents a SLAM (Simultaneous Localization and Mapping) method which builds 2D grid maps and generates the OctoMap based on Rao-Blackwellized particle filters. This work combines wheeled odometry and laser scan with particle filter algorithm to get the pose of the robot, and at the same time fuses the data of depth camera to generate OctoMap, OctoMap is an integrated open source framework based on octree, which is well known for its memory efficiency for the representation of 3D environments. The traditional 3D point cloud map cannot be applied in robot navigation. But OctoMap is a 3D occupancy grid mapping, which can be applied to 3D path planning of flying robots and other robots that are equipped with manipulators. In short, the experimental results demonstrate that the proposed methods can make a robot to synchronize building 2D and 3D maps very efficiently.
Year
DOI
Venue
2018
10.1109/ICACI.2018.8377487
2018 Tenth International Conference on Advanced Computational Intelligence (ICACI)
Keywords
Field
DocType
SLAM,rao-blackwellized particle filters,gmapping,2D grid map,octoMap
Motion planning,Computer vision,Computer science,Particle filter,Odometry,Artificial intelligence,Simultaneous localization and mapping,Robot,Mobile robot,Octree,Occupancy grid mapping
Conference
ISBN
Citations 
PageRank 
978-1-5386-4363-1
0
0.34
References 
Authors
3
7
Name
Order
Citations
PageRank
Li Yao15320.09
Zhun Fan232435.30
Guijie Zhu300.34
Wenji Li400.34
Chong Li5227.35
Yupeng Wang600.34
Honghui Xie700.34