CPA SLAM: Consistent plane model alignment for direct RGB D SLAM
Planes are predominant features of man made environments which have been exploited in many mapping approaches. In this paper, we propose a real time capable RGB D SLAM system that consistently integrates frame to keyframe and frame to plane alignment. Our method models the environment with a global plane model and besides direct image alignment it uses the planes for tracking and global graph optimization. This way, our method makes use of the dense image information available in keyframes for accurate short term tracking. At the same time it uses a global model to reduce drift. Both components are integrated consistently in an expectation maximization framework. In experiments, we demonstrate the benefits our approach and its state of the art accuracy on challenging benchmarks.
2016 IEEE International Conference on Robotics and Automation (ICRA)