부산대학교 도서관

This work presents KMVO, a ground plane based visual odometry that utilizes the vehicle's kinematic model to improve accuracy and robustness. Instead of solving a generic image alignment problem, the motion parameters of a differential drive vehicle can be directly estimated from RGB- D image data. In addition, a method for outlier rejection is presented that can deal with large percentages of outliers. The system is designed to run in real time on a single thread of a mobile CPU. The results of the proposed method are compared to other publicly available visual odometry and SLAM methods on a set of nine real world image sequences of different indoor environments.