Abstract
In indoor environments, there exists a few distinctive indoor spaces' features (ISFs). However, up to our knowledge, there is no algorithm that fully utilizes ISF for accurate 3-D SLAM. In this letter, we suggest a sensor system that efficiently captures ISF and propose an algorithm framework that accurately estimates sensor's 3-D poses by utilizing ISF. Experiments conducted in six representative indoor spaces show that the accuracy of the proposed method is better than the previous method. Furthermore, the proposed method shows robust performances in a sense that a set of adjusted parameters of the related algorithms does not need to be recalibrated as target environment changes. We also demonstrate that the proposed method not only generates 3-D depth maps but also builds a dense 3-D RGB-D map.
Original language | English |
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Article number | 7378318 |
Pages (from-to) | 316-323 |
Number of pages | 8 |
Journal | IEEE Robotics and Automation Letters |
Volume | 1 |
Issue number | 1 |
DOIs | |
Publication status | Published - 2016 Jan 1 |
Keywords
- Localization
- Mapping
- SLAM
ASJC Scopus subject areas
- Control and Systems Engineering
- Human-Computer Interaction
- Biomedical Engineering
- Mechanical Engineering
- Control and Optimization
- Artificial Intelligence
- Computer Science Applications
- Computer Vision and Pattern Recognition