Onboard Autonomy on the Intelligent Payload Experiment CubeSat Mission

Steve Ankuo Chien, J. Doubleday, D. Thompson, K. Wagstaff, J. Bellardo, Craig Francis, Eric Baumgarten, Austin Williams, Edmund Yee, E. Stanton, Jordi Piug-Suari
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引用次数: 57

Abstract

The Intelligent Payload Experiment (IPEX) is a CubeSat that flew from December 2013 through January 2015 and validated autonomous operations for onboard instrument processing and product generation for the Intelligent Payload Module of the Hyperspectral Infrared Imager (HyspIRI) mission concept. IPEX used several artificial intelligence technologies. First, IPEX used machine learning and computer vision in its onboard processing. IPEX used machine-learned random decision forests to classify images onboard (to downlink classification maps) and computer vision visual salience software to extract interesting regions for downlink in acquired imagery. Second, IPEX flew the Continuous Activity Scheduler Planner Execution and Re-planner AI planner/scheduler onboard to enable IPEX operations to replan to best use spacecraft resources such as file storage, CPU, power, and downlink bandwidth. First, the ground and flight operations concept for proposed HyspIRI IPM operations is described, followed by a description ...
智能载荷实验立方体卫星任务的机载自主性
智能有效载荷实验(IPEX)是一颗立方体卫星,于2013年12月至2015年1月飞行,验证了高光谱红外成像仪(HyspIRI)任务概念的智能有效载荷模块的机载仪器处理和产品生成的自主操作。IPEX使用了几种人工智能技术。首先,IPEX在其机载处理中使用了机器学习和计算机视觉。IPEX使用机器学习随机决策森林对机载图像进行分类(下行分类地图),并使用计算机视觉视觉显著性软件在获取的图像中提取感兴趣的区域进行下行。其次,IPEX搭载了Continuous Activity Scheduler Planner Execution和Re-planner人工智能规划/调度程序,使IPEX的操作能够重新规划,以最好地利用航天器资源,如文件存储、CPU、电源和下行链路带宽。首先,描述了提出的HyspIRI IPM操作的地面和飞行操作概念,然后描述了HyspIRI IPM操作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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