Event-based Lunar OPtical flow Egomotion estimation (ELOPE) Challenge: Dataset, Competition Design and Results

Event-based vision is a promising technology with incredible potential for future space exploration. The Event-based Lunar OPtical flow Egomotion estimation (ELOPE) Challenge aims at evaluating and comparing approaches for lunar landing egomotion estimation using data from a single event-based camera. This work is based on the ELOPE Dataset, which is the first publicly available event-based camera dataset for lunar landing. Over 44 teams participated, with 21 reaching the final leaderboard. After submitting 132 solutions, only the top three teams achieved performance surpassing the frame-based baseline. The main contribution of this paper is the comparison of these top three competitors submissions, and a broader analysis of the main challenges in neuromorphic vision for autonomous lunar landing.