@inproceedings{3000efb7d5484f8194afdaf37d8ae1b8,
title = "3D FastSLAM algorithm with Kinect sensor",
abstract = "The FastSLAM is a fundamental algorithm for autonomous mobile robots Simultaneous Localization and Mapping (SLAM) problem. Until now, FastSLAM has been implemented in two-dimensional environment case and grid map is popular choice for constructing the map. This paper presents a new FastSLAM system to estimate the robot trajectory and reconstruct three-dimensional environments. This 3D FastSLAM algorithm uses both Rao-Blackwellized particle filtering and voxel map. Each scan of 3D range sensor provides accurate measurements likelihood using binary Bayes filter. We implemented the hardware system based on the Pioneer 2-DX platform equipped with one Microsoft Kinect sensor. The proposed method can be applied with any 3D range sensors and experimental results show that the proposed method builds a 3D OctoMap and estimates the robot's pose accurately.",
keywords = "3D Range Sensor, 3D SLAM, FastSLAM, Voxel Map",
author = "Hyunggi Jo and Sungjin Jo and Euntai Kim and Changyong Yoon and Sewoong Jun",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 Joint 7th International Conference on Soft Computing and Intelligent Systems, SCIS 2014 and 15th International Symposium on Advanced Intelligent Systems, ISIS 2014 ; Conference date: 03-12-2014 Through 06-12-2014",
year = "2014",
month = feb,
day = "18",
doi = "10.1109/SCIS-ISIS.2014.7044862",
language = "English",
series = "2014 Joint 7th International Conference on Soft Computing and Intelligent Systems, SCIS 2014 and 15th International Symposium on Advanced Intelligent Systems, ISIS 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "214--217",
booktitle = "2014 Joint 7th International Conference on Soft Computing and Intelligent Systems, SCIS 2014 and 15th International Symposium on Advanced Intelligent Systems, ISIS 2014",
address = "United States",
}