An FPGA Acceleration and Optimization Techniques for 2D LiDAR SLAM Algorithm-Reference-Cited by-同舟云学术

An FPGA Acceleration and Optimization Techniques for 2D LiDAR SLAM Algorithm

Published:2021-06-01 Issue:6 Volume:E104.D Page:789-800
ISSN:0916-8532
Container-title:IEICE Transactions on Information and Systems
language:en
Short-container-title:IEICE Trans. Inf. & Syst.

Author:

SUGIURA Keisuke¹,MATSUTANI Hiroki¹

Affiliation:

1. Graduate School of Science and Technology, Keio University

Publisher

Institute of Electronics, Information and Communications Engineers (IEICE)

Subject

Artificial Intelligence,Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Hardware and Architecture,Software

Link

https://www.jstage.jst.go.jp/article/transinf/E104.D/6/E104.D_2020EDP7174/_pdf

Reference30 articles.

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2. [2] M. Montemerlo, S. Thrun, D. Koller, and B. Wegbreit, “FastSLAM: A Factored Solution to the Simultaneous Localization and Mapping Problem,” Proc. AAAI National Conference on Artificial Intelligence, pp.593-598, 2002.

3. [3] M. Montemerlo, S. Thrun, D. Koller, and B. Wegbreit, “FastSLAM 2.0: An Improved Particle Filtering Algorithm for Simultaneous Localization and Mapping that Provably Converges,” Proc. International Joint Conference on Artificial Intelligence (IJCAI), pp.1151-1156, June 2003.

4. [4] G. Grisetti, C. Stachniss, and W. Burgard, “Improved Techniques for Grid Mapping with Rao-Blackwellized Particle Filters,” IEEE Trans. Robot., vol.23, no.1, pp.32-46, March 2007. 10.1109/tro.2006.889486

5. [5] J.M. Santos, D. Portugal, and R.P. Rocha, “An evaluation of 2D SLAM techniques available in Robot Operating System,” Proc. IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), pp.1-6, Oct. 2013. 10.1109/ssrr.2013.6719348

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