Journal of Robotics, Networking and Artificial Life

Volume 3, Issue 2, September 2016, Pages 102 - 106

Attitude/Position Estimation of Rigid-Body using Inertial and Vision Sensors

Authors
Shihao Sun, Yingmin Jia
Corresponding Author
Shihao Sun
Available Online 1 September 2016.
DOI
10.2991/jrnal.2016.3.2.8How to use a DOI?
Keywords
attitude and position estimation, EKF, inertial sensor, vision sensor.
Abstract

This paper is concerned with the attitude/position estimation of a rigid-body using inertial and vision sensors. By employing the Newton-Euler method, a kinematic model is developed for the rigid-body by treating the inertial measurements as inputs. Based on the coordinate transformation, a nonlinear visual observation model is proposed by using the image coordinates of feature points as observations. Then the Extended Kalman filter (EKF) is utilized to estimate the attitude/position recursively. The effectiveness of the proposed algorithm is evaluated by simulation.

Copyright
© 2013, 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/).

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Journal
Journal of Robotics, Networking and Artificial Life
Volume-Issue
3 - 2
Pages
102 - 106
Publication Date
2016/09/01
ISSN (Online)
2352-6386
ISSN (Print)
2405-9021
DOI
10.2991/jrnal.2016.3.2.8How to use a DOI?
Copyright
© 2013, 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/).

Cite this article

TY  - JOUR
AU  - Shihao Sun
AU  - Yingmin Jia
PY  - 2016
DA  - 2016/09/01
TI  - Attitude/Position Estimation of Rigid-Body using Inertial and Vision Sensors
JO  - Journal of Robotics, Networking and Artificial Life
SP  - 102
EP  - 106
VL  - 3
IS  - 2
SN  - 2352-6386
UR  - https://doi.org/10.2991/jrnal.2016.3.2.8
DO  - 10.2991/jrnal.2016.3.2.8
ID  - Sun2016
ER  -