EKF Based Pose Estimation using Two Back-to-Back Stereo Pairs

Abstract

In this work, we solve the pose estimation problem for robot motion by placing multiple cameras on the robot. In particular, we use four cameras arranged as two back-to-back stereo pairs combined with the extended Kalman filter (EKF). The reason for using multiple cameras is that the pose estimation problem is more constrained for multiple cameras than for a single camera. Back-to-back cameras are used since they provide more information. Stereo information is used in self initialization and outlier rejection. Different approaches to solve the long-sequence-drift have been suggested. Both the simulations and the real experiments show that our approach is fast, robust, and accurate.