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This paper presents a preliminary design for a real-time monocular odometry system tailored for planetary rovers, leveraging asynchronous event cameras to address computational constraints and challenging lighting conditions. The approach uses an Error-State Kalman Filter (ESKF) to estimate camera ego-motion based on asynchronous events. The system integrates RATE, a real-time asynchronous feature tracker, to provide continuous updates to the camera state.
Event cameras and asynchronous feature tracking might be the key to robust, low-power odometry for planetary exploration under extreme conditions.
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.