事件相机+卡尔曼滤波，实现实时异步单目里程计
Design of a Real-time Asynchronous Monocular Odometry for Planetary Exploration
- 基于事件相机的异步数据流，实时跟踪特征点
- 在微秒级精度下实现相机位姿估计，适配火星探测算力约束
- 对极端光照变化鲁棒，适合复杂行星表面探索
我们提出一种面向行星探测的实时异步事件相机单目里程计初步设计。在计算资源严格受限的条件下，行星漫游车常面临复杂多变、不可预测的环境，需高帧率感知与强动态范围（HDR）光照下的鲁棒性。事件相机通过以微秒级分辨率异步报告像素亮度变化，大幅降低数据带宽，同时保持在极端光照条件下的稳定性。本文方法基于误差状态卡尔曼滤波器（ESKF），利用该异步事件流持续估计相机自身运动。相机状态随RATE（一种实时异步特征追踪器）输出的每个跟踪位置进行更新。
原文摘要 · Abstract (English)
We describe our preliminary design of a real-time asynchronous event-based monocular odometry for planetary exploration. Operating under strict computational constraints, planetary rovers frequently encounter complex, unpredictable environments that demand high-speed sensing and robustness to high dynamic range (HDR) lighting. Event cameras address these needs by reporting asynchronous, pixel-wise brightness changes with microsecond resolution, significantly reducing data bandwidth while maintaining robustness in extreme lighting conditions. We propose an approach based on an Error-State Kalman Filter (ESKF) that leverages this asynchronous event stream to continuously estimate camera ego-motion. The camera state is updated with every tracked position output generated by RATE, a real-time asynchronous feature tracker.
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