论文标题
使用无人机和机器学习成功恢复观察到的陨石跌落
Successful Recovery of an Observed Meteorite Fall Using Drones and Machine Learning
论文作者
论文摘要
我们报告使用无人机和机器学习算法首次恢复新鲜的陨石跌落。沙漠火球网络在2021年4月1日在西澳大利亚州观察到了一场火球，为预测的幸存弥撒计算了一个秋季区域。一个搜索团队到达现场，并在4天的时间内对5.1 km2区域进行了调查。每次飞行后，经过融合的陨石对陨石的陨石进行了培训，每次飞行后都在现场计算机上处理图像。由该算法确定的陨石候选者使用两个用户界面进行了分类，以消除误报。尚存的候选人用较小的无人机重新审视，并以更高的分辨率成像，然后被淘汰或最终被人工访问。使用这种方法的有效性，将在计算出的秋季线的50 m内回收70 g陨石，这将有助于有效地收集更多更多观察到的陨石瀑布。
We report the first-time recovery of a fresh meteorite fall using a drone and a machine learning algorithm. A fireball on the 1st April 2021 was observed over Western Australia by the Desert Fireball Network, for which a fall area was calculated for the predicted surviving mass. A search team arrived on site and surveyed 5.1 km2 area over a 4-day period. A convolutional neural network, trained on previously-recovered meteorites with fusion crusts, processed the images on our field computer after each flight. meteorite candidates identified by the algorithm were sorted by team members using two user interfaces to eliminate false positives. Surviving candidates were revisited with a smaller drone, and imaged in higher resolution, before being eliminated or finally being visited in-person. The 70 g meteorite was recovered within 50 m of the calculated fall line using, demonstrating the effectiveness of this methodology which will facilitate the efficient collection of many more observed meteorite falls.
