Enhanced Indoor Navigation Using Fusion of IMU and RGB-D Camera

DOI

10.2991/cisia-15.2015.149How to use a DOI?

Keywords

Inertial measurement unit (IMU); Visual gyroscope; Direction cosine Matrix (DCM); Iterative closest point (ICP); Kalman filtering

Abstract

Accurate indoor navigation, especially precise attitude estimation is a challenge topic. Unlike the rate gyroscope in an IMU, the camera based visual-gyro does not suffer from drift errors. In order to overcome the drawbacks of the standalone systems, an INS/visual-gyro integration using direction cosine matrix (DCM) models is presented. Compared to the conventional Euler angle models, the usage of DCM can provide linear system models and avoided singularity problems. Using iterative closest point (ICP) algorithm, the depth measurement from a RGB-D camera can be converted to positioning information and further added to the integrated navigation system. To show the performance of the presented system, one field experiment is carried out with a mobile robot and the numerical results are shown.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - W.N Chai
AU  - C. Chen
AU  - E. Edwan
PY  - 2015/06
DA  - 2015/06
TI  - Enhanced Indoor Navigation Using Fusion of IMU and RGB-D Camera
BT  - Proceedings of the International Conference on Computer Information Systems and Industrial Applications
PB  - Atlantis Press
SP  - 547
EP  - 549
SN  - 2352-538X
UR  - https://doi.org/10.2991/cisia-15.2015.149
DO  - 10.2991/cisia-15.2015.149
ID  - Chai2015/06
ER  -