Semi-Direct Ekf-Based Monocular Visual-Inertial Odometry
2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)(2015)
摘要
We propose a novel monocular visual inertial odometry algorithm that combines the advantages of EKF-based approaches with those of direct photometric error minimization methods. The method is based on sparse, very small patches and incorporates the minimization of photometric error directly into the EKF measurement model so that inertial data and vision-based surface measurements are used simultaneously during camera pose estimation. We fuse vision-based and inertial measurements almost at the raw-sensor level, allowing the estimated system state to constrain and guide image-space measurements. Our formulation allows for an efficient implementation that runs in real-time on a standard CPU and has several appealing and unique characteristics such as being robust to fast camera motion, in particular rotation, and not depending on the presence of corner-like features in the scene. We experimentally demonstrate robust and accurate performance compared to ground truth and show that our method works on scenes containing only non-intersecting lines.
更多查看译文
关键词
semi-direct EKF-based monocular visual-inertial odometry,monocular visual inertial odometry algorithm,direct photometric error minimization methods,EKF measurement model,vision-based surface measurements,camera pose estimation,vision-based measurements,inertial measurements,raw-sensor level,image-space measurements,corner-like features
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络