An efficient likelihood field mapping method and high speed scan matching method using it

Author:

MATSUNAGA Mitsuhiro1,NAKAZAWA Kazuo1

Affiliation:

1. Faculty of Science and Technology, Keio University

Publisher

Japan Society of Mechanical Engineers

Reference20 articles.

1. Abdelrasoul, Y., Saman, A.B.S.H. and Sebastian, P., A quantitative study of tuning ROS Gmapping parameters and their effect on performing indoor 2D SLAM, Proceeding of International symposium on Robotics and Manufacturing Automation (ROMA) (2016), DOI:10.1109/ROMA.2016.7847825.

2. Besl, J.P. and Mckay, D.N., A method for registration of 3-d shapes, IEEE Transaction on Pattern Analysis and Machine Intelligence,Vol.14, No.2 (1992), pp.239-256.

3. Blanco, J.L., Gonzalez, J. and Fernandez-Madrigal, J.A., An optimal filtering algorithm for non-parametric observation models in robot localization, Proceeding of IEEE International Conference on Robotics and Automation (ICRA) (2008).

4. Champleboux, G., Lavallee, S., Szeliski, R. and Brinie, L., From accurate range image sensor calibration to accurate model - based 3D object localization, Proceeding of IEEE Computer Vision and Pattern Recognition (CVPR1992) (1992), pp.83-89.

5. Dellaert, F., Fox, D., Burgard, W. and Thrun, S., Monte carlo localization for mobile robots, Proceeding of International conference on Robotics and Automation in Mishigan (1999), pp.1322-1328.

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