This letter proposes an efficient visual-inertial estimator for aerial robots. The main contribution lies in the direct use of intensity measurements of the latest image frames and key frame via both continuous and regular homographic relations under an assumption of a single planar scene. The filter-based method provides comprehensive estimates of position and attitude with notable efficiency and robustness. The flight evaluation indicates that the incorporation of keyframes significantly minimizes the estimation drift while retaining accurate estimates of flight velocity. Compared to state-of-the-art methods, the proposed work provides rivalling performance at substantially lower computational cost by taking the advantage of the assumed single planar structure.

中文翻译：

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使用单平面原语的 MAV 的高效迭代基于 EKF 的直接视觉惯性里程计

这封信为空中机器人提出了一种有效的视觉惯性估计器。主要贡献在于在单个平面场景的假设下，通过连续和规则单应关系直接使用最新图像帧和关键帧的强度测量。基于滤波器的方法以显着的效率和鲁棒性提供位置和姿态的综合估计。飞行评估表明，关键帧的结合显着减少了估计漂移，同时保留了对飞行速度的准确估计。与最先进的方法相比，所提出的工作通过利用假定的单一平面结构的优势，以显着降低的计算成本提供了具有竞争力的性能。