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Details for article 3 of 6 found articles
| Title: |
Map building without localization by estimation of inter-feature distances |
| Author: |
Ueta, Atsushi Yairi, Takehisa Kanazaki, Hirofumi Machida, Kazuo |
| Appeared in: |
Intelligent data analysis |
| Paging: | Volume 14 (2010) nr. 4 pages 515-529 |
| Year: |
2010-07-26 |
| Contents: |
This paper proposes an alternative solution to a mapping problem in two different cases; when bearing measurements to features (landmarks) and odometry are measured and when bearing and range measurements to features are measured. Our approach named M-SEIFD (Mapping by Sequential Estimation of Inter-Feature Distances) first estimates inter-feature distances, then finds global position of all the features by enhanced multi-dimensional scaling (MDS). M-SEIFD is different from the conventional SLAM methods based on Bayesian filtering in that robot self-localization is not compulsory and that M-SEIFD is able to utilize prior information about relative distances among features directly. We show that M-SEIFD is able to achieve a decent map of features both in simulation and in real-world environment with a mobile robot. |
| Publisher: |
IOS Press |
| Source file: |
Elektronische Wetenschappelijke Tijdschriften |
Details for article 3 of 6 found articles
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