TY  - JOUR
AB  - Purpose– Positioning is a key task in most field robotics applications but can be very challenging in GPS‐denied or high‐slip environments. The purpose of this paper is to describe a visual odometry strategy using only one camera in country roads.Design/methodology/approach– This monocular odometery system uses as input only those images provided by a single camera mounted on the roof of the vehicle and the framework is composed of three main parts: image motion estimation, ego‐motion computation and visual odometry. The image motion is estimated based on a hyper‐complex wavelet phase‐derived optical flow field. The ego‐motion of the vehicle is computed by a blocked RANdom SAmple Consensus algorithm and a maximum likelihood estimator based on a 4‐degrees of freedom motion model. These as instantaneous ego‐motion measurements are used to update the vehicle trajectory according to a dead‐reckoning model and unscented Kalman filter.Findings– The authors' proposed framework and algorithms are validated on videos from a real automotive platform. Furthermore, the recovered trajectory is superimposed onto a digital map, and the localization results from this method are compared to the ground truth measured with a GPS/INS joint system. These experimental results indicate that the framework and the algorithms are effective.Originality/value– The effective framework and algorithms for visual odometry using only one camera in country roads are introduced in this paper.
VL  - 38
IS  - 5
SN  - 0143-991X
DO  - 10.1108/01439911111154081
UR  - https://doi.org/10.1108/01439911111154081
AU  - Wang Cailing
AU  - Zhao Chunxia
AU  - Yang Jingyu
PY  - 2011
Y1  - 2011/01/01
TI  - Monocular odometry in country roads based on phase‐derived optical flow and 4‐DOF ego‐motion model
T2  - Industrial Robot: An International Journal
PB  - Emerald Group Publishing Limited
SP  - 509
EP  - 520
Y2  - 2024/05/10
ER  -