TY - GEN
T1 - Observability analysis of a vision-aided inertial navigation system using planar features on the ground
AU - Panahandeh, Ghazaleh
AU - Guo, Chao X.
AU - Jansson, Magnus
AU - Roumeliotis, Stergios I.
PY - 2013
Y1 - 2013
N2 - In this paper, we present an observability analysis of a vision-aided inertial navigation system (VINS) in which the camera is downward looking and observes a single point feature on the ground. In our analysis, the full INS parameter vector (including position, velocity, rotation, and inertial sensor biases) as well as the 3D position of the observed point feature are considered as state variables. In particular, we prove that the system has only three unobservable directions corresponding to global translations along the x and y axes, and rotations around the gravity vector. Hence, compared to general VINS, an advantage of using only ground features is that the vertical translation becomes observable. The findings of the theoretical analysis are validated through real-world experiments.
AB - In this paper, we present an observability analysis of a vision-aided inertial navigation system (VINS) in which the camera is downward looking and observes a single point feature on the ground. In our analysis, the full INS parameter vector (including position, velocity, rotation, and inertial sensor biases) as well as the 3D position of the observed point feature are considered as state variables. In particular, we prove that the system has only three unobservable directions corresponding to global translations along the x and y axes, and rotations around the gravity vector. Hence, compared to general VINS, an advantage of using only ground features is that the vertical translation becomes observable. The findings of the theoretical analysis are validated through real-world experiments.
UR - http://www.scopus.com/inward/record.url?scp=84893775956&partnerID=8YFLogxK
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U2 - 10.1109/IROS.2013.6696956
DO - 10.1109/IROS.2013.6696956
M3 - Conference contribution
AN - SCOPUS:84893775956
SN - 9781467363587
T3 - IEEE International Conference on Intelligent Robots and Systems
SP - 4187
EP - 4194
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 -