有效载荷(计算)
正方体卫星
计算机科学
电信线路
航空电子设备
星座
人工智能
嵌入式系统
实时计算
工程类
电信
卫星
计算机网络
航空航天工程
物理
网络数据包
天文
作者
Steve Chien,Joshua Doubleday,David R. Thompson,Kiri L. Wagstaff,John Bellardo,C. R. Francis,Eric Baumgarten,Austin Williams,Edmund Yee,Eric J. Stanton,Jordi Piug-Suari
出处
期刊:Journal of aerospace information systems
[American Institute of Aeronautics and Astronautics]
日期:2016-04-18
卷期号:14 (6): 307-315
被引量:49
摘要
This article is a part of the Special Issue on Intelligent Systems for Space Exploration. 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 the ground and flight operations concept used for the IPEX mission to validate key elements of automation for the proposed HyspIRI IPM operations concept. The use of machine learning, computer vision, and automated planning onboard IPEX is also described. The results from the over-1-year flight of the IPEX mission are reported.
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