Pub Date : 2023-03-04DOI: 10.1109/AERO55745.2023.10115887
K. J. Foo, M. Tissera, R. D. Tan, K. S. Low
With the advanced development and maturing of small satellite technologies, there is a high commercial demand for low-cost small satellites with fast delivery for a multitude of applications. This paper presents a hardware-in-the-loop system for testing the satellite's attitude determination and control system and the Agile framework from software engineering practices to guide resource-effective end-to-end development processes, while maintaining a comprehensive system validation. Experimental results for design verification of satellite's Attitude Determination and Control Systems (ADCS) using our ongoing concurrent multiple satellite programs are presented.
{"title":"Agile Development of Small Satellite's Attitude Determination and Control System","authors":"K. J. Foo, M. Tissera, R. D. Tan, K. S. Low","doi":"10.1109/AERO55745.2023.10115887","DOIUrl":"https://doi.org/10.1109/AERO55745.2023.10115887","url":null,"abstract":"With the advanced development and maturing of small satellite technologies, there is a high commercial demand for low-cost small satellites with fast delivery for a multitude of applications. This paper presents a hardware-in-the-loop system for testing the satellite's attitude determination and control system and the Agile framework from software engineering practices to guide resource-effective end-to-end development processes, while maintaining a comprehensive system validation. Experimental results for design verification of satellite's Attitude Determination and Control Systems (ADCS) using our ongoing concurrent multiple satellite programs are presented.","PeriodicalId":344285,"journal":{"name":"2023 IEEE Aerospace Conference","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116677025","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}
Pub Date : 2023-03-04DOI: 10.1109/AERO55745.2023.10115547
E. Some, A. Gasiewski
This paper explores the potential benefits of combining the use of injection-locking techniques with GPS signals as a common clock source when applied to a low-cost Software Defined Radio (SDR) to improve the accuracy of coherent multiple receivers. Coherent systems impose severe requirements on the frequency stability of the signal source at the receiver. In this work, injection-locked oscillators are used as local clock receivers, which inherently synchronizes the SDR analog digital converter (ADCs) sampling times and keeps the local oscillator locked on to the GPS stimulus periodic signal. This paper illustrates the hardware modifications needed for to the injection locking oscillators of eight RTL-SDR radios and the theory behind it, and experimentally measures the degree of coherency in the frequency, phase and time synchronization to verify the proposed method. The coherency demonstrated in the results prove the feasibility of using beamforming, multiple input multiple output (MIMO) and RF transmitter geo-localization.
{"title":"Software Defined Radio Injection-Locking using a GPS signal for multichannel coherent receivers","authors":"E. Some, A. Gasiewski","doi":"10.1109/AERO55745.2023.10115547","DOIUrl":"https://doi.org/10.1109/AERO55745.2023.10115547","url":null,"abstract":"This paper explores the potential benefits of combining the use of injection-locking techniques with GPS signals as a common clock source when applied to a low-cost Software Defined Radio (SDR) to improve the accuracy of coherent multiple receivers. Coherent systems impose severe requirements on the frequency stability of the signal source at the receiver. In this work, injection-locked oscillators are used as local clock receivers, which inherently synchronizes the SDR analog digital converter (ADCs) sampling times and keeps the local oscillator locked on to the GPS stimulus periodic signal. This paper illustrates the hardware modifications needed for to the injection locking oscillators of eight RTL-SDR radios and the theory behind it, and experimentally measures the degree of coherency in the frequency, phase and time synchronization to verify the proposed method. The coherency demonstrated in the results prove the feasibility of using beamforming, multiple input multiple output (MIMO) and RF transmitter geo-localization.","PeriodicalId":344285,"journal":{"name":"2023 IEEE Aerospace Conference","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115452222","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}
Pub Date : 2023-03-04DOI: 10.1109/AERO55745.2023.10115552
Andrew Choate, D. Harris, T. Nickens, Paul D. Kessler, M. Simon
As NASA prepares for the next human footsteps on the lunar surface, the Agency is already looking ahead to systems that will enable a sustained human presence on the lunar surface and mission to Mars, including a lunar Surface Habitat (SH) and Mars Transit Habitat (TH). This paper describes the latest NASA government reference design for the TH and how it will support NASA's Moon to Mars human exploration architecture. First, it will serve as a test and demonstration platform in lunar orbit, demonstrating capabilities required for long-duration microgravity human spaceflight as part of the lunar-Mars analog missions. Then, the TH will serve as a major Mars exploration element to support crew habitation during their transit from the Earth's orbit to Mars and returning safely before TH's return to a lunar orbit. This paper will cover several considerations contributing to the latest habitat design refinement, including the TH's concept of operations, system functional definition, subsystem assumptions, notional interior layouts, a detailed mass and volume breakdown, and identify future trade studies and analyses required to close identified technology/ development/architecture gaps. In addition to a technical description of the TH, this paper describes how the current TH government reference design will achieve many of the current lunar and Mars mission goals. Additionally, there are many assumed technological advances needed to support the prescribed mission phases leading up to the crewed mission to Mars in the late 2030s. The paper will describe many of the TH systems requiring further technology development and identify architectural solutions to achieve these mass, reliability, autonomy, and crew health targets. As a whole, the data shows the government reference TH design meeting the 26.4 metric ton launch /trans-Mars injection burn control mass limit outlined within NASA's Moon to Mars Campaign. This is achievable near the desired timeframe with moderate strategic investments including maintainable life support systems, innovative structures configuration and materials, and system/ logistics packaging. The resulting design detail and data contained in this paper are intended to help teams across NASA and potential commercial, academic, or international partners understand the current performance targets of the Transit Habitat and vehicle interface considerations imposed by the latest Moon to Mars mission scope.
{"title":"NASA's Moon to Mars (M2M) Transit Habitat Refinement Point of Departure Design","authors":"Andrew Choate, D. Harris, T. Nickens, Paul D. Kessler, M. Simon","doi":"10.1109/AERO55745.2023.10115552","DOIUrl":"https://doi.org/10.1109/AERO55745.2023.10115552","url":null,"abstract":"As NASA prepares for the next human footsteps on the lunar surface, the Agency is already looking ahead to systems that will enable a sustained human presence on the lunar surface and mission to Mars, including a lunar Surface Habitat (SH) and Mars Transit Habitat (TH). This paper describes the latest NASA government reference design for the TH and how it will support NASA's Moon to Mars human exploration architecture. First, it will serve as a test and demonstration platform in lunar orbit, demonstrating capabilities required for long-duration microgravity human spaceflight as part of the lunar-Mars analog missions. Then, the TH will serve as a major Mars exploration element to support crew habitation during their transit from the Earth's orbit to Mars and returning safely before TH's return to a lunar orbit. This paper will cover several considerations contributing to the latest habitat design refinement, including the TH's concept of operations, system functional definition, subsystem assumptions, notional interior layouts, a detailed mass and volume breakdown, and identify future trade studies and analyses required to close identified technology/ development/architecture gaps. In addition to a technical description of the TH, this paper describes how the current TH government reference design will achieve many of the current lunar and Mars mission goals. Additionally, there are many assumed technological advances needed to support the prescribed mission phases leading up to the crewed mission to Mars in the late 2030s. The paper will describe many of the TH systems requiring further technology development and identify architectural solutions to achieve these mass, reliability, autonomy, and crew health targets. As a whole, the data shows the government reference TH design meeting the 26.4 metric ton launch /trans-Mars injection burn control mass limit outlined within NASA's Moon to Mars Campaign. This is achievable near the desired timeframe with moderate strategic investments including maintainable life support systems, innovative structures configuration and materials, and system/ logistics packaging. The resulting design detail and data contained in this paper are intended to help teams across NASA and potential commercial, academic, or international partners understand the current performance targets of the Transit Habitat and vehicle interface considerations imposed by the latest Moon to Mars mission scope.","PeriodicalId":344285,"journal":{"name":"2023 IEEE Aerospace Conference","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115592378","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}
Pub Date : 2023-03-04DOI: 10.1109/AERO55745.2023.10115800
Qian Shi, W. Tsutsui, I. Walter, Jitesh H. Panchal, D. DeLaurentis
The space industry has seen promising advancements in additive manufacturing (AM) technologies, including the production of rocket engines and spacecraft components. Nevertheless, AM adoption decisions are still complex due to the many considerations, uncertainties, and stakeholders involved. This paper proposes and demonstrates a decision support framework – including a utility theory-based decision engine that was developed in-house – to support users in evaluating AM-use options. The key decision attributes (i.e., performance, cost, and time) of a space satellite bracket assembly were identified through a requirements definition process. Utility functions representing different decision-maker risk preferences were defined based on relevant spacecraft operating conditions. Attribute data for machine-material pair options were also quantified using data sheets, AM cost, and build-time models. The utility functions, attribute values, and attribute weights were input to the decision engine software for a machine-material pair recommendation. A sensitivity analysis was conducted by varying the utility functions, attribute weights, build volume, and applying “hard constraints”. The results demonstrated the versatility and applicability of the decision framework and engine in tackling AM machine-material pair selection problems, including for the satellite design and manufacturing use case.
{"title":"A Decision Support Framework for Additive Manufacturing of Space Satellite Systems","authors":"Qian Shi, W. Tsutsui, I. Walter, Jitesh H. Panchal, D. DeLaurentis","doi":"10.1109/AERO55745.2023.10115800","DOIUrl":"https://doi.org/10.1109/AERO55745.2023.10115800","url":null,"abstract":"The space industry has seen promising advancements in additive manufacturing (AM) technologies, including the production of rocket engines and spacecraft components. Nevertheless, AM adoption decisions are still complex due to the many considerations, uncertainties, and stakeholders involved. This paper proposes and demonstrates a decision support framework – including a utility theory-based decision engine that was developed in-house – to support users in evaluating AM-use options. The key decision attributes (i.e., performance, cost, and time) of a space satellite bracket assembly were identified through a requirements definition process. Utility functions representing different decision-maker risk preferences were defined based on relevant spacecraft operating conditions. Attribute data for machine-material pair options were also quantified using data sheets, AM cost, and build-time models. The utility functions, attribute values, and attribute weights were input to the decision engine software for a machine-material pair recommendation. A sensitivity analysis was conducted by varying the utility functions, attribute weights, build volume, and applying “hard constraints”. The results demonstrated the versatility and applicability of the decision framework and engine in tackling AM machine-material pair selection problems, including for the satellite design and manufacturing use case.","PeriodicalId":344285,"journal":{"name":"2023 IEEE Aerospace Conference","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115658601","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}
Pub Date : 2023-03-04DOI: 10.1109/AERO55745.2023.10115609
A. Holloway, Jonathan Denison, Neel Patel, M. Maimone, A. Rankin
The Mars Science Laboratory (MSL) Curiosity rover is about to receive its sixth and likely final complete flight software update after having operated on Mars for more than a decade. Software transitions on MSL provide an opportunity to add or replace functionality, fix bugs, and prepare for future capabilities. The penultimate full software release, R12, was installed on Curiosity in 2015, three years after its August 2012 landing, and was followed over the subsequent seven years by many patches as engineers worked to address new mission constraints quickly. Because each additional patch increases the complexity of maintaining and operating the rover, a new flight software update called R13 was proposed, which aimed to make operations more straightforward by incorporating existing patches, improved software capabilities, and new software capabilities into a single monolithic rover flight software image. The R13 development effort kicked off in early 2017. Over the next six years, the scope of R13 expanded to include many desired capabilities and bug fixes - some of which were proposed even earlier than 2015 but were unable to be implemented in R12. Overall, the MSL Change Control Board approved 56 bug fixes and 53 new features for R13 development. Twenty-seven developers implemented these changes over a 3.5-year period. Following a 2.25-year testing campaign, R13 was approved for use in flight onboard Curiosity. In this paper, we detail the path of the R13 flight software release from its proposal in April 2016 to its approval for use in flight in September 2022.
{"title":"Six Years and 184 Tickets: The Vast Scope of the Mars Science Laboratory's Ultimate Flight Software Release","authors":"A. Holloway, Jonathan Denison, Neel Patel, M. Maimone, A. Rankin","doi":"10.1109/AERO55745.2023.10115609","DOIUrl":"https://doi.org/10.1109/AERO55745.2023.10115609","url":null,"abstract":"The Mars Science Laboratory (MSL) Curiosity rover is about to receive its sixth and likely final complete flight software update after having operated on Mars for more than a decade. Software transitions on MSL provide an opportunity to add or replace functionality, fix bugs, and prepare for future capabilities. The penultimate full software release, R12, was installed on Curiosity in 2015, three years after its August 2012 landing, and was followed over the subsequent seven years by many patches as engineers worked to address new mission constraints quickly. Because each additional patch increases the complexity of maintaining and operating the rover, a new flight software update called R13 was proposed, which aimed to make operations more straightforward by incorporating existing patches, improved software capabilities, and new software capabilities into a single monolithic rover flight software image. The R13 development effort kicked off in early 2017. Over the next six years, the scope of R13 expanded to include many desired capabilities and bug fixes - some of which were proposed even earlier than 2015 but were unable to be implemented in R12. Overall, the MSL Change Control Board approved 56 bug fixes and 53 new features for R13 development. Twenty-seven developers implemented these changes over a 3.5-year period. Following a 2.25-year testing campaign, R13 was approved for use in flight onboard Curiosity. In this paper, we detail the path of the R13 flight software release from its proposal in April 2016 to its approval for use in flight in September 2022.","PeriodicalId":344285,"journal":{"name":"2023 IEEE Aerospace Conference","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123667498","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}
Pub Date : 2023-03-04DOI: 10.1109/AERO55745.2023.10115656
Annmarie Spexet, Jessica LaRocco-Olszewski, D. Alvord
In the aviation space, maintenance is the main driver in the push for Internet of Things (loT) device management systems, artificial intelligence (AI)/machine learning (ML) re-search, and cloud infrastructure. The potential for this approach to reduce downtime, maximize component lifetime, re-duce man-hours on diagnosis and repair, and optimize supply chains and scheduling has driven massive investments across the industry. And yet, the challenges in delivering on these promises with the available data and technology should also not be minimized. To reach its full potential, maintenance program implementers must understand what predictions can be derived from the available data, what maintenance actions may be driven by those predictions, and how the predictions should be presented to the appropriate decision makers in ground operations and the logistics chain. This report examines the current state of data within the aviation maintenance space, variations in component level coverage, and how that translates to the type, volume, and timeliness of data and computational infrastructure necessary to provide right time predictions and analytics to maintainers, supply chain managers, and operators. This report also addresses some of the specific challenges in the aviation space with respect to data availability, equipment variability, use variability, and maintenance action coding that can affect the ability of operators to derive value from a data science program.
{"title":"Data Pipeline Considerations for Aviation Maintenance","authors":"Annmarie Spexet, Jessica LaRocco-Olszewski, D. Alvord","doi":"10.1109/AERO55745.2023.10115656","DOIUrl":"https://doi.org/10.1109/AERO55745.2023.10115656","url":null,"abstract":"In the aviation space, maintenance is the main driver in the push for Internet of Things (loT) device management systems, artificial intelligence (AI)/machine learning (ML) re-search, and cloud infrastructure. The potential for this approach to reduce downtime, maximize component lifetime, re-duce man-hours on diagnosis and repair, and optimize supply chains and scheduling has driven massive investments across the industry. And yet, the challenges in delivering on these promises with the available data and technology should also not be minimized. To reach its full potential, maintenance program implementers must understand what predictions can be derived from the available data, what maintenance actions may be driven by those predictions, and how the predictions should be presented to the appropriate decision makers in ground operations and the logistics chain. This report examines the current state of data within the aviation maintenance space, variations in component level coverage, and how that translates to the type, volume, and timeliness of data and computational infrastructure necessary to provide right time predictions and analytics to maintainers, supply chain managers, and operators. This report also addresses some of the specific challenges in the aviation space with respect to data availability, equipment variability, use variability, and maintenance action coding that can affect the ability of operators to derive value from a data science program.","PeriodicalId":344285,"journal":{"name":"2023 IEEE Aerospace Conference","volume":"105 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125389861","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}
Pub Date : 2023-03-04DOI: 10.1109/AERO55745.2023.10115852
Cesare Guariniello, D. DeLaurentis
Decision makers face a difficult task when planning large-scale space missions or long-term development of technologies for space systems architectures. The difficulties arise from multiple factors. First, the size of the problem, the diversity of the involved systems and technologies, and the variety of stakeholders and their needs result in a large a complex trade space. Second, technologies are continuously evolving, and it can be hard to find data and model for new technologies, which increases the uncertainty about availability and performance. Third, in these complex problems decision makers need to account not only for traditional engineering trade-off (including cost, time, performance, and risk) but also for policies, stakeholder preferences, and flexibility of space architectures. Building on our previous research in System-of-Systems methodologies, we propose a combination of tools to support decision-making for technology prioritization and analysis of development time, risk, and flexibility of space architectures. Based on developmental dependencies between technologies, Technology Readiness Level (TRL), mission requirements, uncertainty, cost, and budget limitations, the tools produce the optimal expected schedule and allow the user to identify potential bottleneck and risks. Different strategies for prioritization of technologies can also be compared. The tools can handle constraints such as policies or stakeholder preferences, which impose prioritization of certain technologies or space missions. Finally, since long-term space mission planning is very dynamic and its specific objectives change often, we implemented tools to add analysis of flexibility on top of the technology prioritization tools. This analysis is performed from different perspectives. From a mission viewpoint, given a selected mission category (and its associated technologies), we assess how difficult it is to transition to a different mission, in terms of cost and number of technologies that are missing, as well as evaluating differences in cost. From a programmatic viewpoint, we quantify flexibility of specific technology prioritization schedules when decisions to switch to a different mission arise.
{"title":"Technology Prioritization and Architecture Flexibility for Space System-of-Systems","authors":"Cesare Guariniello, D. DeLaurentis","doi":"10.1109/AERO55745.2023.10115852","DOIUrl":"https://doi.org/10.1109/AERO55745.2023.10115852","url":null,"abstract":"Decision makers face a difficult task when planning large-scale space missions or long-term development of technologies for space systems architectures. The difficulties arise from multiple factors. First, the size of the problem, the diversity of the involved systems and technologies, and the variety of stakeholders and their needs result in a large a complex trade space. Second, technologies are continuously evolving, and it can be hard to find data and model for new technologies, which increases the uncertainty about availability and performance. Third, in these complex problems decision makers need to account not only for traditional engineering trade-off (including cost, time, performance, and risk) but also for policies, stakeholder preferences, and flexibility of space architectures. Building on our previous research in System-of-Systems methodologies, we propose a combination of tools to support decision-making for technology prioritization and analysis of development time, risk, and flexibility of space architectures. Based on developmental dependencies between technologies, Technology Readiness Level (TRL), mission requirements, uncertainty, cost, and budget limitations, the tools produce the optimal expected schedule and allow the user to identify potential bottleneck and risks. Different strategies for prioritization of technologies can also be compared. The tools can handle constraints such as policies or stakeholder preferences, which impose prioritization of certain technologies or space missions. Finally, since long-term space mission planning is very dynamic and its specific objectives change often, we implemented tools to add analysis of flexibility on top of the technology prioritization tools. This analysis is performed from different perspectives. From a mission viewpoint, given a selected mission category (and its associated technologies), we assess how difficult it is to transition to a different mission, in terms of cost and number of technologies that are missing, as well as evaluating differences in cost. From a programmatic viewpoint, we quantify flexibility of specific technology prioritization schedules when decisions to switch to a different mission arise.","PeriodicalId":344285,"journal":{"name":"2023 IEEE Aerospace Conference","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121438719","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}
Pub Date : 2023-03-04DOI: 10.1109/AERO55745.2023.10115732
Raunak Srivastava, Rolif Lima, Roshan Sah, K. Das
Use of autonomous space robots show promising potential for precise in-orbit proximity operations like in-orbit servicing and debris capture. However, manipulators mounted on board a satellite present a highly complex and nonlinear dynamic system, which is hence difficult to control for precise in-orbit tasks. We had, in our previous work, presented a Non-linear Model Predictive Controller (NMPC) for Free Floating and Rotation Floating space robots in order to design an optimal path that the end-effector can follow while being controlled to reach the target. However, the MPC optimization problem has to be solved online with the requirement of obtaining the solution within the specified loop rate for a stable performance. Due to the high computational time taken by the MPC's optimization routine, the update frequency of MPC becomes a limiting factor when deployed even on moderately complex hardware systems. This led us to modify the existing controller and use a parameterized Neural Network based controller which learns the optimal policy from the MPC solution. Accordingly, in this work, we solve the optimal control problem via Iterative Linear Quadratic Regulator (iLQR) and use it as means to train a Neural Network (NN) policy online. The final control value for the space robot is hence a weighted combination of the control efforts obtained from the iLQR and NN policy. The accuracy of the proposed modification to a conventional Model Predictive controller and its ability to perform the control objective is demonstrated.
{"title":"In-Orbit Control of Floating Space Robots using a Model Dependant Learning Based Methodology","authors":"Raunak Srivastava, Rolif Lima, Roshan Sah, K. Das","doi":"10.1109/AERO55745.2023.10115732","DOIUrl":"https://doi.org/10.1109/AERO55745.2023.10115732","url":null,"abstract":"Use of autonomous space robots show promising potential for precise in-orbit proximity operations like in-orbit servicing and debris capture. However, manipulators mounted on board a satellite present a highly complex and nonlinear dynamic system, which is hence difficult to control for precise in-orbit tasks. We had, in our previous work, presented a Non-linear Model Predictive Controller (NMPC) for Free Floating and Rotation Floating space robots in order to design an optimal path that the end-effector can follow while being controlled to reach the target. However, the MPC optimization problem has to be solved online with the requirement of obtaining the solution within the specified loop rate for a stable performance. Due to the high computational time taken by the MPC's optimization routine, the update frequency of MPC becomes a limiting factor when deployed even on moderately complex hardware systems. This led us to modify the existing controller and use a parameterized Neural Network based controller which learns the optimal policy from the MPC solution. Accordingly, in this work, we solve the optimal control problem via Iterative Linear Quadratic Regulator (iLQR) and use it as means to train a Neural Network (NN) policy online. The final control value for the space robot is hence a weighted combination of the control efforts obtained from the iLQR and NN policy. The accuracy of the proposed modification to a conventional Model Predictive controller and its ability to perform the control objective is demonstrated.","PeriodicalId":344285,"journal":{"name":"2023 IEEE Aerospace Conference","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125189829","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}
Pub Date : 2023-03-04DOI: 10.1109/AERO55745.2023.10115558
Siwei Zhang, Pedro Fernandez Ruz, Fabio Broghammer, E. Staudinger, C. Gentner, R. Pöhlmann, A. Dammann, Manuel Schütt, R. Lichtenheldt
At the Institute of Communications and Navigation of the German Aerospace Center (DLR), we have studied and developed radio-based swarm navigation technologies for a decade. In this paper, we provide a complete solution of ultra-wide band (UWB) localization network for a robotic swarm. This network is organized in a fully decentralized fashion and resilient to clock imperfections, topology changes, packet loss and the hidden node problem. In this network, a multitude of active devices and an arbitrary number of passive devices can exploit the UWB signals for self-localization, i.e. estimating their relative positions and orientations, without sophisticated clock and antenna calibration, which dramatically simplifies the de-sign and manufacturing of such a swarm. Our proposed solution is verified with experiments and was successfully demonstrated in a space-analogue multi-robot surface exploration mission on the volcano Mt. Etna, Sicily, Italy, in July 2022.
{"title":"Self-Organized UWB Localization for Robotic Swarm – First Results from an Analogue Mission on Volcano Etna","authors":"Siwei Zhang, Pedro Fernandez Ruz, Fabio Broghammer, E. Staudinger, C. Gentner, R. Pöhlmann, A. Dammann, Manuel Schütt, R. Lichtenheldt","doi":"10.1109/AERO55745.2023.10115558","DOIUrl":"https://doi.org/10.1109/AERO55745.2023.10115558","url":null,"abstract":"At the Institute of Communications and Navigation of the German Aerospace Center (DLR), we have studied and developed radio-based swarm navigation technologies for a decade. In this paper, we provide a complete solution of ultra-wide band (UWB) localization network for a robotic swarm. This network is organized in a fully decentralized fashion and resilient to clock imperfections, topology changes, packet loss and the hidden node problem. In this network, a multitude of active devices and an arbitrary number of passive devices can exploit the UWB signals for self-localization, i.e. estimating their relative positions and orientations, without sophisticated clock and antenna calibration, which dramatically simplifies the de-sign and manufacturing of such a swarm. Our proposed solution is verified with experiments and was successfully demonstrated in a space-analogue multi-robot surface exploration mission on the volcano Mt. Etna, Sicily, Italy, in July 2022.","PeriodicalId":344285,"journal":{"name":"2023 IEEE Aerospace Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114609021","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}
Pub Date : 2023-03-04DOI: 10.1109/AERO55745.2023.10115988
Z. Miller, Brayden Stidham, T. Fairbanks, Carlos Maldonado
Stereolithography (SLA) Additive Manufacturing (AM) is a fabrication technique in which three dimensional parts are made by selectively curing layers of the part in a vat of UV photopolymer resin. Because this process is performed at near ambient temperature, unlike laser sintering or direct melting techniques, and there is minimal contact with the final part during the build such as for polymer extrusion methods, SLA manufacturing produces parts with low applied stress throughout the build. This allows highly complex geometries, tight tolerances, fine surface finish, and detailed features to be readily achieved. The process is not without drawbacks, however. The SLA process generally only produces polymer parts which are undesirable for space applications due to effects such as outgassing, charge accumulation, and creep. Additionally, the SLA resins must be formulated to cure with UV exposure which leads to compromises when compared with conventionally produced polymers. Finally, AM methods in general have less well-defined material properties, exhibit geometry dependent material properties, and are anisotropic. This work examines five commercially available materials to assess their usefulness in space-based instrumentation. The materials are chosen to span a variety of material properties including strength, temperature rating, resolution, and opacity. Utilization of these materials requires consideration of the materials' response to the harshness of the space environment, particularly with respect to vacuum and ionizing radiation which is not data readily available from the manufacturer. As such, experimental outgassing data is presented on each material with and without a vacuum prebake. The response to ionizing radiation is then considered for a high-resolution SLA material that is being used in an upcoming CubeSat mission in GTO. Samples make from this material are subjected to ionizing radiation from a Cs137 source to absorbed doses up to 10 Mrad. Tensile and flexural testing is performed on these samples and the change in mechanical properties relative to radiation does is characterized. Current applications of the material are then explored, including the silicon detector holder that will be flown on the upcoming ESRA CubeSat mission. The detector holder, made of a high-resolution SLA material, locates the detectors and provides provisions for wire routing and vacuum venting on a miniaturized scale. The use of SLA allows this part to be manufactured quickly and affordably with features that would not be possible using conventional manufacturing techniques. Lastly, ongoing work is presented including characterizing additional materials ionizing radiation response and investigating the potential to metallize SLA parts.
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