Robust cooperative visual localization with experimental validation for unmanned aerial vehicles

This article aims to present an adaptive and robust cooperative visual localization solution based on stereo vision systems. With the proposed solution, a group of unmanned vehicles, either aerial or ground will be able to construct a large reliable map and localize themselves precisely in this map without any user intervention. For this cooperative localization and mapping problem, a robust nonlinear H∞ filter is adapted to ensure robust pose estimation. In addition, a robust approach for feature extraction and matching based on an adaptive scale invariant feature transform stereo constrained algorithm is implemented to build a large consistent map. Finally, a validation of the solution proposed is presented and discussed using simulation and experimental data.

Record URL:
Record URL:
Availability:
- Find a library where document is available. Order URL: http://worldcat.org/oclc/19966973
Supplemental Notes:
- Reprinted by permission of Sage Publications, Ltd.
Authors:
- Nemra, Abdelkrim
- Aouf, Nabil
Publication Date: 2013-12

Language

English

Media Info

Media Type: Print
Features: Figures; Photos; References;
Pagination: pp 1892-1910
Serial:
- Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering
- Volume: 227
- Issue Number: 12
- Publisher: Sage Publications, Incorporated
- ISSN: 0954-4100
- EISSN: 2041-3025
- Serial URL: http://pig.sagepub.com/

Subject/Index Terms

TRT Terms: Algorithms; Data fusion; Detection and identification systems; Drones; Flight simulators; Mapping; Vision
Uncontrolled Terms: Robustness; Simultaneous localization and mapping (SLAM)
Subject Areas: Aviation; Data and Information Technology; Vehicles and Equipment; I91: Vehicle Design and Safety;

Filing Info

Accession Number: 01498871
Record Type: Publication
Files: TRIS
Created Date: Nov 12 2013 9:17AM