James N. Martin, Ryan A. Noguchi, R. Minnichelli, Marilee J. Wheaton
{"title":"Implementing Enterprise Systems Engineering Enabled by the Digital Engineering Approach","authors":"James N. Martin, Ryan A. Noguchi, R. Minnichelli, Marilee J. Wheaton","doi":"10.2514/6.2020-4218","DOIUrl":"https://doi.org/10.2514/6.2020-4218","url":null,"abstract":"","PeriodicalId":153489,"journal":{"name":"ASCEND 2020","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133077480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Performance Analysis of Hierarchical Reinforcement Learning Framework for Stochastic Space Logistics","authors":"Yuji Takubo, Hao Chen, K. Ho","doi":"10.2514/6.2020-4230","DOIUrl":"https://doi.org/10.2514/6.2020-4230","url":null,"abstract":"","PeriodicalId":153489,"journal":{"name":"ASCEND 2020","volume":"210 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114008405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Greenhouse Architecture Analysis in Partial Gravity of Mars and Moon","authors":"M. M. Esfandabadi, O. Bannova","doi":"10.2514/6.2020-4262","DOIUrl":"https://doi.org/10.2514/6.2020-4262","url":null,"abstract":"","PeriodicalId":153489,"journal":{"name":"ASCEND 2020","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123085797","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ezinne Uzo-Okoro, Daniel Erkel, P. Manandhar, M. Dahl, Emily Kiley, K. Cahoy, O. Weck
On-orbit assembly missions typically involve humans-in-the-loop and use large custom-built robotic arms designed to service existing modules. A proposed concept of on-orbit robotic assembly of modularized CubeSat components within a spacecraft locker eliminates the need for humans-in-the loop. The spacecraft locker supports use cases such as rapidly placing failed nodes within a constellation of satellites and providing sensing and propulsion capabilities in Low Earth Orbit. Despite the recent proliferation of small satellites, there are few planned demonstrations of on-orbit assembly and few demonstrations of on-orbit servicing. Key gaps challenges of in-space assembly of small satellites are (1) the lack of standardization of electromechanical CubeSat components for compatibility with commercial robotic assembly hardware, and (2) testing and modifying commercial robotic assembly hardware. In this work, we focus on testing and modifying: we develop an optimization process for a robotic assembly model to integrate small satellites in space. Our process focus is on the optimization of the on-orbit assembly time of small satellites. We use Commercial-Off-The-Shelf (COTS) robot arms to snap together components in a spacecraft, while minimizing humans-in-the-loop. Assembly time is the selected performance metric as it is critical to the assertion that building small satellites on-orbit results in reduced budget and satellite development time on Earth. We minimize on-orbit small satellite assembly time by optimizing assembly time with the Genetic Algorithm, which use dexterous robotic arms to assemble components, without any negative effects on the attitude and control system. We implement a robot arm assembly model in Python, using Inverse Kinematics. We use a Genetic Algorithm-based optimization scheme, with time as the objective function, and three constraints: robot assembly volume, power consumption, and peak power. Design variables such as joint damping, motor force (torque), position gain and velocity gain are used to model grasping a component and moving the component to the satellite assembly area of the spacecraft. The robot arms are required to be within a tolerance defined based on the 300 mm x 300 mm x 500 mm assembly area. In simulation, we observe that using a given baseline servo motor (7 V) at high proportional gains results in optimal assembly time of approximately 10-20 seconds per component assembly, compared to roughly double this time per component for a 1U CubeSat weighing 2 kg. However, we expect this improvement to result in 25% higher power consumption. Using a high gain value with a lower voltage (5 V) motor results in oscillations and additional time required to dampen out to within the given tolerance, and results in increased assembly time. The benchmarked small satellite assembly time with a human-in-the-loop requires 50 weeks to 90 months of component assembly and integration time on Earth. We anticipate that on-orbit a
在轨装配任务通常涉及人在环，并使用大型定制机械臂来为现有模块提供服务。提出了在航天器储物柜内对模块化立方体卫星组件进行在轨机器人组装的概念，消除了对人类参与回路的需要。航天器储物柜支持用例，例如在卫星星座中快速放置故障节点，并在低地球轨道上提供传感和推进能力。尽管最近小卫星大量增加，但很少有计划的在轨装配演示和在轨服务演示。小卫星空间装配面临的主要挑战是:(1)缺乏与商用机器人装配硬件兼容的机电CubeSat组件标准化;(2)测试和修改商用机器人装配硬件。在这项工作中，我们的重点是测试和修改:我们开发了一个机器人装配模型的优化过程，以集成空间中的小卫星。我们的过程重点是小卫星在轨装配时间的优化。我们使用商用现货(COTS)机器人手臂来将航天器中的组件组装在一起，同时最大限度地减少了人工参与。装配时间是选择的性能指标，因为它对于在轨道上建造小型卫星会减少预算和地球上的卫星开发时间的断言至关重要。采用遗传算法优化小卫星在轨装配时间，在不影响姿态和控制系统的前提下，利用灵巧的机械臂对部件进行装配。我们利用逆运动学在Python中实现了一个机器人手臂装配模型。采用基于遗传算法的优化方案，以时间为目标函数，设定机器人装配量、功耗和峰值功率三个约束条件。利用关节阻尼、电机力(转矩)、位置增益和速度增益等设计变量对抓取部件并将部件移动到航天器的卫星装配区域进行建模。机械臂要求在基于300 mm x 300 mm x 500 mm装配区域定义的公差范围内。在模拟中，我们观察到，在高比例增益下使用给定的基准伺服电机(7 V)，每个组件组装的最佳装配时间约为10-20秒，相比之下，重量为2公斤的1U CubeSat每个组件的装配时间大约是该时间的两倍。然而，我们预计这一改进将导致25%的高功耗。使用较低电压(5 V)电机的高增益值会导致振荡，并且需要额外的时间来抑制到给定公差范围内，并导致组装时间增加。以人在环的小型卫星装配时间为基准，在地球上需要50周到90个月的部件装配和集成时间。我们预计，对于总功率为30w的1u功能立方体卫星，优化的在轨装配能力将使装配时间减少一个数量级。对于1 U CubeSat装配，我们显示机器人装配时间节省了42%。
{"title":"Optimization of On-Orbit Robotic Assembly of Small Satellites","authors":"Ezinne Uzo-Okoro, Daniel Erkel, P. Manandhar, M. Dahl, Emily Kiley, K. Cahoy, O. Weck","doi":"10.2514/6.2020-4195","DOIUrl":"https://doi.org/10.2514/6.2020-4195","url":null,"abstract":"On-orbit assembly missions typically involve humans-in-the-loop and use large custom-built robotic arms designed to service existing modules. A proposed concept of on-orbit robotic assembly of modularized CubeSat components within a spacecraft locker eliminates the need for humans-in-the loop. The spacecraft locker supports use cases such as rapidly placing failed nodes within a constellation of satellites and providing sensing and propulsion capabilities in Low Earth Orbit. Despite the recent proliferation of small satellites, there are few planned demonstrations of on-orbit assembly and few demonstrations of on-orbit servicing. Key gaps challenges of in-space assembly of small satellites are (1) the lack of standardization of electromechanical CubeSat components for compatibility with commercial robotic assembly hardware, and (2) testing and modifying commercial robotic assembly hardware. In this work, we focus on testing and modifying: we develop an optimization process for a robotic assembly model to integrate small satellites in space. Our process focus is on the optimization of the on-orbit assembly time of small satellites. We use Commercial-Off-The-Shelf (COTS) robot arms to snap together components in a spacecraft, while minimizing humans-in-the-loop. Assembly time is the selected performance metric as it is critical to the assertion that building small satellites on-orbit results in reduced budget and satellite development time on Earth. We minimize on-orbit small satellite assembly time by optimizing assembly time with the Genetic Algorithm, which use dexterous robotic arms to assemble components, without any negative effects on the attitude and control system. We implement a robot arm assembly model in Python, using Inverse Kinematics. We use a Genetic Algorithm-based optimization scheme, with time as the objective function, and three constraints: robot assembly volume, power consumption, and peak power. Design variables such as joint damping, motor force (torque), position gain and velocity gain are used to model grasping a component and moving the component to the satellite assembly area of the spacecraft. The robot arms are required to be within a tolerance defined based on the 300 mm x 300 mm x 500 mm assembly area. In simulation, we observe that using a given baseline servo motor (7 V) at high proportional gains results in optimal assembly time of approximately 10-20 seconds per component assembly, compared to roughly double this time per component for a 1U CubeSat weighing 2 kg. However, we expect this improvement to result in 25% higher power consumption. Using a high gain value with a lower voltage (5 V) motor results in oscillations and additional time required to dampen out to within the given tolerance, and results in increased assembly time. The benchmarked small satellite assembly time with a human-in-the-loop requires 50 weeks to 90 months of component assembly and integration time on Earth. We anticipate that on-orbit a","PeriodicalId":153489,"journal":{"name":"ASCEND 2020","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128928089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Assemblers: A Modular, Reconfigurable Manipulator for Autonomous in-Space Assembly","authors":"John Cooper, J. Neilan, M. Mahlin, Laura M. White","doi":"10.2514/6.2020-4132","DOIUrl":"https://doi.org/10.2514/6.2020-4132","url":null,"abstract":"","PeriodicalId":153489,"journal":{"name":"ASCEND 2020","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128534139","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Collin Deans, Theresa C. Furgiuele, Daniel D. Doyle, Jonathan T. Black
{"title":"Simulating Omni-Directional Aerial Vehicle Operations for Modeling Satellite Dynamics","authors":"Collin Deans, Theresa C. Furgiuele, Daniel D. Doyle, Jonathan T. Black","doi":"10.2514/6.2020-4023","DOIUrl":"https://doi.org/10.2514/6.2020-4023","url":null,"abstract":"","PeriodicalId":153489,"journal":{"name":"ASCEND 2020","volume":"107 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116808497","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Architecture Options for Creation of a Persistent Platform Orbital Testbed","authors":"Doggett William","doi":"10.2514/6.2020-4130","DOIUrl":"https://doi.org/10.2514/6.2020-4130","url":null,"abstract":"","PeriodicalId":153489,"journal":{"name":"ASCEND 2020","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115668633","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The Pulsed Fission-Fusion (PuFF) Engine - Nacelle Concept and Development Roadmap","authors":"R. Adams, J. Cassibry, K. Schillo, Brian Taylor","doi":"10.2514/6.2020-4082","DOIUrl":"https://doi.org/10.2514/6.2020-4082","url":null,"abstract":"","PeriodicalId":153489,"journal":{"name":"ASCEND 2020","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115788220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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