TY - GEN
T1 - IMU-RGBD camera navigation using point and plane features
AU - Guo, Chao X.
AU - Roumeliotis, Stergios
PY - 2013
Y1 - 2013
N2 - In this paper, we present a linear-complexity 3D inertial navigation algorithm using both point and plane features observed from an RGBD camera. In particular, we study the system's observability properties, and prove that: (i) When observing a single plane feature of known direction, the IMU gyroscope bias is observable. (ii) By observing a single point feature, as well as a single plane of known direction but not perpendicular to gravity, all degrees of freedom of the IMU-RGBD navigation system become observable, up to global translations. Next, based on the results of the observability analysis, we design a consistency-improved, observability-constrained (OC) extended Kalman filter (EKF)-based estimator for the IMU-RGBD camera navigation system. Finally, we experimentally validate the superiority of our proposed algorithm compared to alternative methods in urban scenes.
AB - In this paper, we present a linear-complexity 3D inertial navigation algorithm using both point and plane features observed from an RGBD camera. In particular, we study the system's observability properties, and prove that: (i) When observing a single plane feature of known direction, the IMU gyroscope bias is observable. (ii) By observing a single point feature, as well as a single plane of known direction but not perpendicular to gravity, all degrees of freedom of the IMU-RGBD navigation system become observable, up to global translations. Next, based on the results of the observability analysis, we design a consistency-improved, observability-constrained (OC) extended Kalman filter (EKF)-based estimator for the IMU-RGBD camera navigation system. Finally, we experimentally validate the superiority of our proposed algorithm compared to alternative methods in urban scenes.
UR - http://www.scopus.com/inward/record.url?scp=84893719823&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84893719823&partnerID=8YFLogxK
U2 - 10.1109/IROS.2013.6696806
DO - 10.1109/IROS.2013.6696806
M3 - Conference contribution
AN - SCOPUS:84893719823
SN - 9781467363587
T3 - IEEE International Conference on Intelligent Robots and Systems
SP - 3164
EP - 3171
BT - IROS 2013
T2 - 2013 26th IEEE/RSJ International Conference on Intelligent Robots and Systems: New Horizon, IROS 2013
Y2 - 3 November 2013 through 8 November 2013
ER -