Probabilistic Egomotion for Stereo Visual Odometry

H. Silva, A. Bernardino, E. Silva
2014 Journal of Intelligent and Robotic Systems  
We present a novel approach of probabilistic egomotion methods for Stereo Visual Odometry using vehicles equipped with calibrated stereo cameras. We combine a dense probabilistic 5D egomotion estimation method with a sparse keypoint based stereo approach to provide high quality estimates of vehicle's angular and linear velocities. To validate our approach, we perform two sets of experiments with a well known benchmarking dataset. First, we assess the quality of the raw velocity estimates in
more » ... arison to classical pose estimation algorithms. Second, we cascade our method's instantaneous velocity estimates with an Extended Kalman Filter and compare its performance results with a well known open source stereo Visual Odometry library. The presented results compare favorably with state-of-the-art approaches, mainly in the estimation of the angular velocities, where significant improvements are achieved.
doi:10.1007/s10846-014-0054-5 fatcat:gsk5znjdsnflxnf7pgxdsstoge