Map completion from partial observation using the global structure of multiple environmental maps-Reference-Cited by-同舟云学术

Map completion from partial observation using the global structure of multiple environmental maps

Published:2022-02-09 Issue:5-6 Volume:36 Page:279-290
ISSN:0169-1864
Container-title:Advanced Robotics
language:en
Short-container-title:Advanced Robotics

Author:

Katsumata Yuki¹,Kanechika Akinori¹,Taniguchi Akira¹^ORCID,El Hafi Lotfi²^ORCID,Hagiwara Yoshinobu¹,Taniguchi Tadahiro¹

Affiliation:

1. College of Information Science and Engineering, Ritsumeikan University, Kusatsu, Shiga, Japan

2. Ritsumeikan Global Innovation Research Organization, Ritsumeikan University, Kusatsu, Shiga, Japan

Funder

Japan Science and Technology Agency

Core Research for Evolutionary Science and Technology

Japan Society for the Promotion of Science (JSPS) KAKENHI

Publisher

Informa UK Limited

Subject

Computer Science Applications,Hardware and Architecture,Human-Computer Interaction,Software,Control and Systems Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/01691864.2022.2029762

Reference31 articles.

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3. Montemerlo M, Thrun S, Koller D, et al. Fastslam: a factored solution to the simultaneous localization and mapping problem. In: Eighteenth National Conference on Artificial Intelligence, Edmonton, Alberta, Canada; 2002. p. 593–598.

4. Montemerlo M, Thrun S, Roller D, et al. Fastslam 2.0: an improved particle filtering algorithm for simultaneous localization and mapping that provably converges. In: Proceedings of the 18th International Joint Conference on Artificial Intelligence; IJCAI'03, Acapulco, Mexico; 2003. p. 1151–1156.

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