Distributed mission operations with the multi-mission encrypted communication system
This paper discusses MECS' architecture for distributed operations and lessons learned from a field test in May 2001.
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This paper discusses MECS' architecture for distributed operations and lessons learned from a field test in May 2001.
After four years on the International Space Station (ISS), the Astrobee Research Facility, has completed over 130 Test Sessions logging over 1000 hours of operations. Managed by the NASA ISS Program OZ office and supported by NASA Ames Research Center (ARC) in California, the Astrobee Team maintains three identical free-flying Astrobee robots for research on the ISS. As a technology demonstration platform, the Astrobee Robots are available for Guest Scientists to use for a spectrum of research capabilities. Astrobee, propelled by battery-operated fans, is designed to autonomously operate throughout most of the USOS (US Orbital Segment), with the objective of minimizing astronaut support. Astrobee carries a suite of six cameras, a two degree-of-freedom (DOF) arm with a gripper that can grasp ISS handrails and other objects, and three payload bays that provide power and data for guest science hardware. Astrobee can autonomously execute hours-long flight plans or be teleoperated from the ground or by astronauts. While the Astrobee Team continues to improve mapping and autonomous flight capabilities, one of the main goals of Astrobee Robots is to provide research opportunities for Guest Scientists. The Astrobee Robot Software (ARS) makes extensive use of the open-source Robot Operating System (ROS). The ARS can be used interchangeably with an Astrobee Simulator or as Astrobee’s onboard software. ARS features include autonomous docking and perching, real-time teleoperations from the ground, plan based autonomous tasks, multi Astrobee communication, among other capabilities. Through simulation software and ground testing laboratories, the Astrobee Team is available to support Guest Scientists during development and testing and lead real-time ISS operations. Guest Scientists can participate in this research opportunity following the Guest Science Lifecycle (GSL) shown in Figure 1: Guest Science Lifecycle below. The Astrobee Team and Guest Scientists have complete research including Gecko materials studies, RFID and sound sensing capabilities, student Robotics Programming Challenges, and Free Flyer formation flight investigations. Current science with the Astrobee Robots includes Free Flyer self-toss studies, new docking capabilities, advanced mapping resolution capabilities, and high resolution panoramic imagery. Future Guest scientists and Astrobee Team research will focus on robotics applications for future NASA missions such as Gateway and Artemis and potential experiments involving human-robot interactions. This presentation will focus on four main subjects, 1) completed, current, and future planned research using the Astrobee robots, 2) how Guest Scientist get from conception to the ISS, 3) Astrobee Facility resources available for Guest Science ground testing and real-time ISS operations support, and 4) lessons learned from four years of ISS operations.
This semester I worked with the Flight Planning Branch at the NASA Johnson Space Center. I learned about the different aspects of flight planning for the International Space Station as well as the software that is used internally and ISSLive! which is used to help educate the public on the space program. I had the opportunity to do on the job training in the Mission Control Center with the planning team. I transferred old timeline records from the planning team's old software to the new software in order to preserve the data for the future when the software is retired. I learned about the operations of the International Space Station, the importance of good communication between the different parts of the planning team, and enrolled in professional development classes as well as technical classes to learn about the space station.
The Cassini Attitude and Articulation Control Subsystem (AACS) Flight Software (FSW) has achieved its intended design goals by successfully guiding and controlling the Cassini-Huygens planetary mission to Saturn and its moons. This paper describes an overview of AACS FSW details from early design, development, implementation, and test to its fruition of operating and maintaining spacecraft control over an eleven year prime mission. Starting from phases of FSW development, topics expand to FSW development methodology, achievements utilizing in-flight autonomy, and summarize lessons learned during flight operations which can be useful to FSW in current and future spacecraft missions.
Proprietary or unique designs and operations are expected early in any industry's development, and often provide a competitive early market advantage. However, there comes a time when a product or industry requires standardization for the whole industry to advance...or survive. For the space industry, that time has come. Here, we will focus on standardization of ground processing for space vehicles and their ground systems. With the retirement of the Space Shuttle, and emergence of a new global space race, affordability and sustainability are more important now than ever. The growing commercialization of the space industry and current global economic environment are driving greater need for efficiencies to save time and money. More RLV's (Reusable Launch Vehicles) are being developed for the gains of reusability not achievable with traditional ELV's (Expendable Launch Vehicles). More crew/passenger vehicles are also being developed. All of this calls for more attention needed for ground processing-repeatedly before launch and after landing/recovery. RLV's should provide more efficiencies than ELV's, as long as MRO (Maintenance, Repair, and Overhaul) is well-planned-even for the unplanned problems. NASA's Space Shuttle is a primary example of an RLV which was supposed to thrive on reusability savings with efficient ground operations, but lessons learned show that costs were (and still are) much greater than expected. International standards and specifications can provide the commonality needed to simplify design and manufacturing as well as to improve safety, quality, maintenance, and operability. There are standards organizations engaged in the space industry, but ground processing is one of the areas least addressed. Challenges are encountered due to various factors often not considered during development. Multiple vehicle elements, sites, customers, and contractors pose various functional and integration difficulties. Resulting technical publication structures and methods are incongruent. Some processing products are still done on paper, some electronic, and many being converted in between. Business systems then are not fully compatible, and paper as well as electronic conversions are time-consuming and costly. NASA and its Shuttle contractors setup rules and systems to handle what has produced over 130 RLV launches, but they have had many challenges. Attempts have been made to apply aviation industry specifications to make the Shuttle more efficient with its ground processing. One efficiency project example was to make a Shuttle Maintenance Manual (SMM) based on the commercial ATA (Air Transport Association of America) Spec 100 for technical publications. This industry standard, along with others, has been a foundation for efficient global MRO of commercial airlines for years. A modified version was also made for some military aircraft. The SMM project found many similarities in Spec 100 which apply to the Shuttle, and room for expansion for space systems/structures not in aircraft. The SMM project team met with the ATA and representatives from NASA's X-33 and X-34 programs to discuss collaboration on a national space standard based on Spec 100. A pilot project was enabled for a subset of Shuttle systems. Full implementation was not yet achieved, X-33 and X-34 were cancelled, and the Shuttles were then designated for retirement. Nonetheless, we can learn from this project how to expand this concept to all space vehicle products. Since then, ATA has joined with ASD (AeroSpace and Defence Industries Association of Europe) and AIA (Aerospace Industries Association) to form a much-enhanced and expanded international specification: Sl000D, International Specification for Technical Publications. It includes air, land, and sea vehicles, missiles, support equipment, ordnance, and communications. It is used by a growing number of countries for commercial and government products. Its modular design is supported by a Common Source Dabase (CSDB), and COTS (commercial off-the-shelf) software is available for production of IETP's (Interactive Electronic Technical Publications). A few space industry products in Europe have begun to apply Sl000D already. Also, there are other related standards/specifications which have global implications. We have an opportunity to adapt Sl000D and possibly other standards for use with space vehicles and ground systems. Sl000D has plenty of flexibility to apply to any product needed. To successfully grow the viability of the space industry, all members, commercial and government, will need to engage cooperatively in developing and applying standards to move toward interoperability. If we leverage and combine the best existing space standards and specifications, develop new ones to address known gaps, and adapt the best applicable features from other industries, we can establish an infrastructure to not only accelerate current development, but also build longevity for a more cohesive international space community.
Programmatic, applicatory, developmental, and operational aspects of sounding rocket utilization for materials processing studies are discussed. Lessons learned through the experience of 10 sounding rocket missions are described. Particular attention is given to missions from the SPAR, Consort, and Joust programs. Successful experiments on Consort include the study of polymer membranes and resins, biological processes, demixing of immiscible liquids, and electrodeposition.
National Aeronautics and Space Administration (NASA) Langley Research Center (LaRC) is spearheading an innovative digital engineering approach to integrate, communicate, and facilitate the research of multi-modal transportation systems. The Knowledge-based Digital Platform (KbDP) is a concept being developed that ties the workflows of Project Managers (PM), Principal Investigators (PI), and System Engineers (SE) together across organizational boundaries. The overarching vision for the KbDP Concept for AAM R&D is a substantial undertaking. The initial concept and implementation will focus on UAM operations to tractably learn and adjust the concept with a manageable database. Lessons learned and best practices with a smaller scope will enable successful scalability to AAM R&D or even to the entire modes of transportation and logistics. The UAM vision is one in which advanced technologies and new operational procedures enable practical and cost-effective air transport as an integrated mode of movement of people and goods throughout metropolitan areas. Initial implementation of three KbDP concepts of use shows promising benefits to NASA’s Air Traffic Management-Exploration (ATM-X) UAM Airspace Subproject. It is envisioned that the KbDP will manage an information database defined by mathematical, data science, and system engineering principles. AIML algorithms play a vital role in this KbDP concept by extracting meaningful knowledge from the information database, which the human user leverages to improve the efficiency and effectiveness of their research greatly.
In this article, we explore the technical details of the reinforcement learning (RL) algorithms that were deployed in the largest field test of automated vehicles designed to smooth traffic flow in history as of 2023, uncovering the challenges and breakthroughs that come with developing RL controllers for automated vehicles. We delve into the fundamental concepts behind RL algorithms and their application in the context of self-driving cars, discussing the developmental process from simulation to deployment in detail, from designing simulators to reward function shaping. We present the results in both simulation and deployment, discussing the flow-smoothing benefits of the RL controller. From understanding the basics of Markov decision processes to exploring advanced techniques such as deep RL, our article offers a comprehensive overview and deep dive of the theoretical foundations and practical implementations driving this rapidly evolving field. We also showcase real-world case studies and alternative research projects that highlight the impact of RL controllers in revolutionizing autonomous driving. From tackling complex urban environments to dealing with unpredictable traffic scenarios, these intelligent controllers are pushing the boundaries of what automated vehicles can achieve. Furthermore, we examine the safety considerations and hardware-focused technical details surrounding deployment of RL controllers into automated vehicles. As these algorithms learn and evolve through interactions with the environment, ensuring their behavior aligns with safety standards becomes crucial. Here, we explore the methodologies and frameworks being developed to address these challenges, emphasizing the importance of building reliable control systems for automated vehicles.
As the assembly of the ISS nears completion, it is worthwhile to step back and review some of the actions pursued by the Program in recent years to reduce risk and enhance the safety and health of ISS crewmembers, visitors, and space flight participants. While the ISS requirements and initial design were intended to provide the best practicable levels of safety, it is always possible to reduce risk -- given the determination and commitment to do so. The following is a summary of some of the steps taken by the ISS Program Manager, by our International Partners, by hardware and software designers, by operational specialists, and by safety personnel to continuously enhance the safety of the ISS. While decades of work went into developing the ISS requirements, there are many things in a Program like the ISS that can only be learned through actual operational experience. These risk reduction activities can be divided into roughly three categories: (1) Areas that were initially noncompliant which have subsequently been brought into compliance or near compliance (i.e., Micrometeoroid and Orbital Debris [MMOD] protection, acoustics) (2) Areas where initial design requirements were eventually considered inadequate and were subsequently augmented (i.e., Toxicity Level 4 materials, emergency hardware and procedures) (3) Areas where risks were initially underestimated, and have subsequently been addressed through additional mitigation (i.e., Extravehicular Activity [EVA] sharp edges, plasma shock hazards) Due to the hard work and cooperation of many parties working together across the span of nearly a decade, the ISS is now a safer and healthier environment for our crew, in many cases exceeding the risk reduction targets inherent in the intent of the original design. It will provide a safe and stable platform for utilization and discovery.
Urban Air Mobility (UAM) aims to reduce congestion on the roads and highways by offering air taxi as an alternative to driving on surface roads. Integration of UAM operations in the National Airspace System (NAS) has been the focus of the research conducted at NASA Ames Research Center. A simulation was performed in collaboration with Uber Technologies Inc to investigate if NASA’s UTM architecture and its implementation as demonstrated in the 2019 UTM field tests were extensible for UAM operations, and if the data exchange between multiple operators as planned under UTM were adequate for UAM operations in the shared airspace. In order to explore these research questions, three Use Cases were defined to investigate different airspace management challenges. This paper will describe the lessons learned from exercising the uses cases and the airspace management services including scheduling and separation developed to facilitate initial UAM operations.
Prior to the launch of the STS-132/ULF4 mission, the International Space Station (ISS) Flight Control Team was alerted to the approach of a space debris with a predicted time of closest approach approximately 1 hr after Space Shuttle docking. As a result, the ISS team considered performing a collision avoidance maneuver prior to the Space Shuttle s approach. The purpose of this presentation will be to use this case study to illustrate best practices of the human spaceflight trajectory operations team. The presentation will begin with an overview of the roles of the real-time ISS and Space Shuttle trajectory flight control teams. Then, the STS-132/ULF4 case study will be used to illustrate the issues and lessons learned involved in performing Space Shuttle rendezvous maneuver planning and execution. Specific elements of the STS-132 Space Shuttle rendezvous maneuver profile that can be used to provide mission assurance in cases of trajectory uncertainty will be described and discussed. Additionally, this case study will be used to provide context for identifying lessons learned in an operational environment that requires technical and decision-making coordination between two control center teams with two potentially maneuvering space vehicles.
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A limiting factor in control system design and analysis for spacecraft is the inability to physically test new algorithms quickly and cheaply. Test flights of space vehicles are costly and take much preparation. As such, EV41 recently acquired a small research quadrocopter that has the ability to be a test bed for new control systems. This project focused on learning how to operate, fly, and maintain the quadrocopter, as well as developing and testing protocols for its use. In parallel to this effort, developing a model in Simulink facilitated the design and analysis of simple control systems for the quadrocopter. Software provided by the manufacturer enabled testing of the Simulink control system on the vehicle.
Most spaceflight crewmembers agree that emergency training is among the most important training they receive. If an emergency event occurs on-orbit crewmembers want to be able to rely on a thorough and proficient knowledge of emergency operations and procedures. The inherent complexity of ISS and the international nature of the onboard operations have resulted in emergency procedures that are complex by any measure; as a result, a very robust apparatus has been developed to give crewmembers initial training on emergency procedures and ensure proficiency up to (and even after) launch. One of the most important aspects of complex onboard operations in general, and emergency operations specifically, is learning how to coordinate roles and responsibilities with fellow crewmembers. A primary goal of NASA s emergency training program is to allow the crewmembers who will actually be together on-orbit to practice executing the emergency responses together before they fly. As with any operation that includes the use of software and hardware, the fidelity of the simulation environment is a critical element to successful training. The NASA training division has spent considerable time and effort to develop a simulator that addresses the most important aspects of emergency response, working within very difficult space and budgetary constraints.
The ability of nuclear reactors to operate their power conversion cycles more flexibly will enhance their value to energy grids with variable pricing. Current nuclear control systems are typically classical controllers that are often based on proportional-integral-derivative (PID) control. This paper presents a method of augmenting the existing PID control for difficult transient operations in nuclear power plants using a reinforcement learning–derived feedforward signal applied in real time. The agents, which are trained on a test thermal load-following problem, are designed to improve steam generator outlet temperature control for a range of fast load-following scenarios covering ramp rates from 9%/min to 15%/min. Several reinforcement learning algorithms were initially investigated for the training of the feedforward agents with deep Q-learning (DQN) and proximal policy optimization (PPO) networks, which were found to be the most promising. The DQN controllers utilize discrete actions, giving them a better disturbance rejection at steady state but inconsistent response to initial temperature deviations. In contrast, PPO-trained agents, which take continuous actions except for a dead zone around zero, were shown to have the best combination of high disturbance rejection at steady state and good tracking of the desired temperature value. The ability of the PPO agent was also examined, with the average time of decision making found to be on the order of 1 ms. The fault properties of the controller under the loss of the reinforcement learning agent feedforward signal were also examined. The controller showed strong performance in situations of “no-signal” faults. but was less good at handling “stuck-at” faults, where the feedforward signal remains at a set value. In both cases, however, the PID was able to successfully maintain stability, eventually returning the system to a steady state. It is hoped that this work will allow for the proposed control architecture to be examined for more difficult control problems such that it may eventually be used to adapt existing nuclear plants for more aggressive load-following on grids of the future.
The Cassini-Huygens Mission to Saturn and Titan, a joint venture between the National Aeronautics and Space Administration, the European Space Agency, and the Italian Space Agency, is conducting a four-year, prime mission exploring the Saturnian system, including its atmosphere, rings, magnetosphere, moons and icy satellites. Launched in 1997, Cassini began its prime mission in 2004. Cassini is now preparing for a new era, a two-year extended mission to revisit many of the highlights and new discoveries made during the prime mission. Because of the light time delay from Earth to Saturn, and the time needed to coordinate the complicated science and engineering activities that take place on the spacecraft, commanding on Cassini is done in approximately 40-day intervals known as sequences. The Cassini Uplink Operations team is responsible for the final development and validation of the pointing profile and instrument and spacecraft commands that are contained in a sequence. During this final analysis prior to uplink to the spacecraft, thorough and exact evaluation is necessary to ensure there are no mistakes during commanding. In order to perform this evaluation, complete and refined processes and procedures are fundamental. The Uplink Operations team is also responsible for anomaly response during sequence execution, a process in which critical decisions often are made in real-time. Recent anomalies on other spacecraft missions have highlighted two major risks in the operations process: (1) personnel turnover and the retirement of critical knowledge and (2) aging, outdated operations procedures. If other missions are a good barometer, the Cassini extended mission will be presented with a high personnel turnover of the Cassini flight team, which could lead to a loss of expertise that has been essential to the success of the prime mission. In order to prepare the Cassini Uplink Operations Team for this possibility and to continue to develop and operate safe science and engineering sequences, a review and major update of the current documentation and operations procedures was needed. This paper will address the changes made to extended mission sequence generation processes primarily due to new restrictions in spacecraft operating capability and lessons learned from prime mission. In addition, it will address the state of the prime mission operations procedures, the philosophy changes and updates that were made to those procedures in response to process improvement, and the validation of those new procedures through the training of current and new personnel. And lastly, it will address the lessons learned throughout prime mission and how the Uplink Operations team chose to incorporate those lessons into the working documentation and team knowledge. This incorporation was necessary to facilitate the success of the extended mission with potentially all new personnel at some point prior to the end of the mission.
The Soil-Moisture Active-Passive (SMAP) spacecraft requires various kinds of in-orbit maneuvers over the course of its three-year mission. The types of maneuvers include pre-planned commissioning maneuvers to reach its science orbit, regularly executed orbit maintenance maneuvers to overcome drag and other nominally occurring phenomena, as well as (the possibility of) collision avoidance maneuvers. The architecture of the spacecraft – in terms of availability of commanding via ground assets, the inherited avionics' ability to sequence and execute commands, and the capability of available subsystems able to carry out maneuvers – was well defined early in the development of the spacecraft and mission, well before the operational plan for responding to maneuver requests was cemented. The systems engineering challenge became: how to accommodate all three types of maneuvers in the confines of this well-defined architecture. This paper will describe how the operations team on SMAP successfully met this challenge. Specifically, it will dive into the three pronged approach that SMAP developed to handle each type of maneuver described above – to meet the timeliness requirements leveraged on the operations team to execute said maneuvers, while continuing to fit within the allotted staffing profile during nominal operations. Defining this paradigm to fit the mission’s architecture meant re-defining the original paradigm, (planned maneuvers being thought of separately than collision avoidance maneuvers), and re-classifying all responses to maneuver requests as variations and permutations of a singular operational response to a maneuver request. This paper will also describe the tools that were created to simplify the human interface and automate as much of the response as was possible. Finally, this paper will describe, at a very high level, some of the problems encountered and lessons learned by the operations team when this process was executed the first four times during the first ninety days of operations. Though the architecture of the operations team's response to maneuver requests will never be repeated exactly, the flexibility that was inserted via redefining the scope of the problem and by redefining the human interfaces should influence future projects' architectures earlier in their development – in the hopes that said influence will save time and money in the future.
The Window Observational Research Facility (WORF) is an ISPR-based rack facility designed to take advantage of the high optical quality US Lab Nadir research window. The WORF is based on the ISS Expedite the Processing of Experiments to Space Station (EXPRESS) rack mechanical structure and electronic systems. The WORF has a unique payload volume located at the center of the rack that provides access to the window. The interior dimensions of the payload volume are 34-in. (86.36 cm) wide by 33-in. (83.82 cm) high by 23-in. (58.42 cm) deep. This facility supports the deployment of payloads such as 9 in. aerial photography cameras and 12 in. diameter optical equipment. The WORF coupled with the optical quality of the United States Lab window support the deployment of various payload disciplines. The WORF provides payloads with power, data command and control, air cooling, water cooling, and video processing. The WORF's payload mounting surfaces and interfaces include the interior payload mounting shelf and the interior and exterior aircraft-like seat tracks. The payload mounting shelf is limited to a maximum mass of 136 kg (299 pounds). The WORF can accommodate large payloads such as the commonly used Leica-Heerbrug RC-30 aerial photography camera (whose dimensions are 53.3 cm (21-in.) wide by 50.8 cm (20-in.) deep by 76.2 cm (30-in.) long). The performance characteristics of the WORF allow it to support an array of payload disciplines. The WORF provides a maximum of 3 Kw at 28 Vdc and has a maximum data rate of 10 Mbps. The WORF's unique payload volume is designed to be light-tight, down to 2.8 x 10(exp -11) Watts/cm2/steradian, and have low-reflective surfaces. This specially designed WORF interior supports payload investigations that observe low-light-level phenomenon such as aurora. Although the WORF rack does not employ any active rack isolation (i.e., vibration dampening) technology, the rack provides a very stable environment for payload operations (on the order of X microradians). The facility's software is capable of being updated during its period of deployment. The WORF project also includes a Suitcase Simulator to allow for a payload developer to verify data interfaces at his development site, a trainer rack for astronauts to learn how to operate the WORF prior to flight, and the use of the EXPRESS Functional Checkout Units to allow for payload checkout at the KSC prior to launch.