Workshop on Autonomy for Future SMD Missions
Summary of the Workshop on Autonomy for Future SMD Missions that was held on July 21, 2017 at the 2017 NASA Exploration Science Forum (Moffett Field, CA).
Fong, Terry↗
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Spacecraft autonomy using onboard processing for a SAR constellation mission
The Autonomous Sciencecraft Experiment (ASE) will fly onboard the Air Force TechSat 21 constellation of three spacecraft scheduled for launch in 2006. ASE uses onboard continuous planning, robust task and goal-based execution, model-based mode identification and reconfiguration, and onboard machine learning and pattem recognition to radically increase science retum by enabling intelligent downlink selection and autonomous retargeting. Demonstration of these capabilities in a flight environment will open up tremendous new opportunities in planetary science, space physics, and earth science that would be unreachable without this technology.
Autonomous Sciencecraft Experiment ASE spacecraft ↗
The Summer Robotic Autonomy Course
We offered a first Robotic Autonomy course this summer, located at NASA/Ames' new NASA Research Park, for approximately 30 high school students. In this 7-week course, students worked in ten teams to build then program advanced autonomous robots capable of visual processing and high-speed wireless communication. The course made use of challenge-based curricula, culminating each week with a Wednesday Challenge Day and a Friday Exhibition and Contest Day. Robotic Autonomy provided a comprehensive grounding in elementary robotics, including basic electronics, electronics evaluation, microprocessor programming, real-time control, and robot mechanics and kinematics. Our course then continued the educational process by introducing higher-level perception, action and autonomy topics, including teleoperation, visual servoing, intelligent scheduling and planning and cooperative problem-solving. We were able to deliver such a comprehensive, high-level education in robotic autonomy for two reasons. First, the content resulted from close collaboration between the CMU Robotics Institute and researchers in the Information Sciences and Technology Directorate and various education program/project managers at NASA/Ames. This collaboration produced not only educational content, but will also be focal to the conduct of formative and summative evaluations of the course for further refinement. Second, CMU rapid prototyping skills as well as the PI's low-overhead perception and locomotion research projects enabled design and delivery of affordable robot kits with unprecedented sensory- locomotory capability. Each Trikebot robot was capable of both indoor locomotion and high-speed outdoor motion and was equipped with a high-speed vision system coupled to a low-cost pan/tilt head. As planned, follow the completion of Robotic Autonomy, each student took home an autonomous, competent robot. This robot is the student's to keep, as she explores robotics with an extremely capable tool in the midst of a new community for roboticists. CMU provided undergraduate course credit for this official course, 16-162U, for 13 students, with all other students receiving course credit from National Hispanic University.
Nourbakhsh, Illah R.↗
Challenges of MSL Entry, Descent, and Landing Validation: Or, "7 Years of Terror"
No abstract available
Mars Science Laboratory↗
Mission Concept Design for Autonomous Space Missions using Mission-Level Modeling and Simulation
NASA’s Europa Lander mission is to search for biosignatures on Europa based on in-situ science using a lander architecture. This mission presents a set of challenges that requires a high level of autonomy on the lander system, leading to the need for a new operational paradigm that supports better collaboration and coordination between the lander and the ground operations team. M\&S is used for both designing the onboard system-level autonomy and the ground operations paradigm that allows effective and efficient collaboration and coordination between the lander and the ground operations team. In this paper, M\&S as applied to the design of new mission and operational concepts will be discussed. At its current early stage of the mission development for Europa Lander, the M\&S is used to explore different mission concepts and gain insights for design (formative) rather than to verify and validate fully designed mission concepts quantitatively (summative). Organically, we established a new approach to mission and operational concept exploration using high-fidelity modeling and simulation. M\&S has been an integral part of the approach of defining constraints and assertions, designing mission concepts, assessing (i.e., simulating them), and discovering insights, which feeds back to the definition an design steps. This organically-established approach provided important benefits to the project at its early phase of the development by enabling the project team to be able to build shared understanding of impacts from design characteristics, constraints, and their interactions on the mission performance.
Ye, Sean↗
Actions, Observations, and Decision-Making: Biologically Inspired Strategies for Autonomous Aerial Vehicles
This paper details the development and demonstration of an autonomous aerial vehicle embodying search and find mission planning and execution srrategies inspired by foraging behaviors found in biology. It begins by describing key characteristics required by an aeria! explorer to support science and planetary exploration goals, and illustrates these through a hypothetical mission profile. It next outlines a conceptual bio- inspired search and find autonomy architecture that implements observations, decisions, and actions through an "ecology" of producer, consumer, and decomposer agents. Moving from concepts to development activities, it then presents the results of mission representative UAV aerial surveys at a Mars analog site. It next describes hardware and software enhancements made to a commercial small fixed-wing UAV system, which inc!nde a ncw dpvelopnent architecture that also provides hardware in the loop simulation capability. After presenting the results of simulated and actual flights of bioinspired flight algorithms, it concludes with a discussion of future development to include an expansion of system capabilities and field science support.
Pisanich, Greg↗
Cognitive Communications for NASA Space Systems
The growing complexity of spacecraft constellations, communication relay offerings, and mission architectures drives the need for the development of autonomous communication systems. NASA has traditionally launched single spacecraft missions that are served by the Space Communication and Navigation (SCaN) program. Operations on SCaN networks are typically scheduled weeks in advance, and often each asset serves a single user spacecraft at a time. Recent movement towards swarm missions could make the current approach unsustainable. Additionally, the integration of commercial communication service providers will substantially increase the data transfer options available to new missions. NASA science missions have found benefit in launching swarms of spacecraft, allowing coordinated simultaneous observations from different perspectives. Inter-spacecraft communication (mesh networking) is an enabler for this architecture, as are CubeSats that allow cost-effective provisioning of distributed mission assets. As more complex swarm missions launch, one challenge is coordinating communication within the swarm and choosing the appropriate mechanism for telemetry, tracking, control, and data services to and from Earth. Cognitive communications research conducted by SCaN aims to mitigate the increasing communication complexity for mission users by increasing the autonomy of links, networks, and service scheduling. By considering automation techniques including recent advances in artificial intelligence and machine learning, cognitive algorithms and related approaches enable increased mission science return, improved resource utilization for service provider networks, and resiliency in unpredictable or unplanned environments. The Cognitive Communications Project at the NASA Glenn Research Center develops applications of data-driven, non-deterministic methods to improve the autonomy of space communication. The project emphasizes development of decentralized space networks with artificial intelligence agents optimizing communication link throughput, data routing, and system-wide asset management. This paper discusses the objectives, approaches, and opportunities of the research to address growing needs of the space communications community.
Chelmins, David↗
Utilizing the ISS Mission as a Testbed to Develop Cognitive Communications Systems
The ISS provides an excellent opportunity for pioneering artificial intelligence software to meet the challenges of real-time communications (comm) link management. This opportunity empowers the ISS Program to forge a testbed for developing cognitive communications systems for the benefit of the ISS mission, manned Low Earth Orbit (LEO) science programs and future planetary exploration programs. In November, 1998, the Flight Operations Directorate (FOD) started the ISS Antenna Manager (IAM) project to develop a single processor supporting multiple comm satellite tracking for two different antenna systems. Further, the processor was developed to be highly adaptable as it supported the ISS mission through all assembly stages. The ISS mission mandated communications specialists with complete knowledge of when the ISS was about to lose or gain comm link service. The current specialty mandated cognizance of large sun-tracking solar arrays and thermal management panels in addition to the highly-dynamic satellite service schedules and rise/set tables. This mission requirement makes the ISS the ideal communications management analogue for future LEO space station and long-duration planetary exploration missions. Future missions, with their precision-pointed, dynamic, laser-based comm links, require complete autonomy for managing high-data rate communications systems. Development of cognitive communications management systems that permit any crew member or payload science specialist, regardless of experience level, to control communications is one of the greater benefits the ISS can offer new space exploration programs. The IAM project met a new mission requirement never previously levied against US space-born communications systems management: process and display the orientation of large solar arrays and thermal control panels based on real-time joint angle telemetry. However, IAM leaves the actual communications availability assessment to human judgment, which introduces unwanted variability because each specialist has a different core of experience with comm link performance. Because the ISS utilizes two different frequency bands, dynamic structure can be occasionally translucent at one frequency while it can completely interdict service at the other frequency. The impact of articulating structure on the comm link can depend on its orientation at the time it impinges on the link. It can become easy for a human specialist to cross-associate experience at one frequency with experience at the other frequency. Additionally, the specialist's experience is incremental, occurring one nine-hour shift at a time. Only the IAM processor experiences the complete 24x7x365 communications link performance for both communications links but, it has no "learning capability." If the IAM processor could be endowed with a cognitive ability to remember past structure-induced comm link outages, based on its knowledge of the ISS position, attitude, communications gear, array joint angles and tracking accuracy, it could convey such experience to the human operator. It could also use its learned communications link behaviors to accurately convey the availability of future communications sessions. Further, the tool could remember how accurately or inaccurately it predicted availability and correct future predictions based on past performance. The IAM tool could learn frequency-specific impacts due to spacecraft structures and pass that information along as "experience." Such development would provide a single artificial intelligence processor that could provide two different experience bases. If it also "knew" the satellite service schedule, it could distinguish structure blockage from schedule or planet blockage and then quickly switch to another satellite. Alternatively, just as a human operator could judge, a cognizant comm system based on the IAM model could "know" that the blockage is not going to last very long and continue tracking a comm satellite, waiting for it to track away from structure. Ultimately, once this capability was fully developed and tested in the Mission Control Center, it could be transferred on-orbit to support development of operations concepts that include more advanced cognitive communications systems. Future applications of this capability are easily foreseen because even more dynamic satellite constellations with more nodes and greater capability are coming. Currently, the ISS fully employs a 300 million bit-per-second (Mbps) return link for harvesting payload science. In the coming eighteen months, it will step up to 600 Mbps. Already there is talk of a 1.2 billion bit-per-second (Gbps) upgrade for the ISS and laser comm links have already been tested from the ISS. Every data rate upgrade mandates more complicated and sensitive communications equipment which implies greater expertise invested in the human operator. Future on-orbit cognizant comm systems will be needed to meet greater performance demands aboard larger, far more complicated spacecraft. In the LEO environment, the old-style one-satellite-per-spacecraft operations concept will give way to a new concept of a single customer spacecraft simultaneously using multiple comm satellites. Much more highly-dynamic manned LEO missions with decades of crew members potentially increase the demand for communications link performance. A cognizant on-board communications system will meet advanced communications demands from future LEO missions and future planetary missions. The ISS has fledgling components of future exploration programs, both LEO and planetary. Further, the Flight Operations Directorate, through the IAM project, has already begun to develop a communications management system that attempts to solve advanced problems ideally represented by dynamic structure impacting scheduled satellite service. With an earnest project to integrate artificial intelligence into the IAM processor, the ISS Program could develop a cognizant communications system that could be adapted and transferred to future on-orbit avionics designs.
Jackson, Dan↗
Utilizing the ISS Mission as a Testbed to Develop Cognitive Communications Systems
The ISS provides an excellent opportunity for pioneering artificial intelligence software to meet the challenges of real-time communications (comm) link management. This opportunity empowers the ISS Program to forge a testbed for developing cognitive communications systems for the benefit of the ISS mission, manned Low Earth Orbit (LEO) science programs and future planetary exploration programs. In November, 1998, the Flight Operations Directorate (FOD) started the ISS Antenna Manager (IAM) project to develop a single processor supporting multiple comm satellite tracking for two different antenna systems. Further, the processor was developed to be highly adaptable as it supported the ISS mission through all assembly stages. The ISS mission mandated communications specialists with complete knowledge of when the ISS was about to lose or gain comm link service. The current specialty mandated cognizance of large sun-tracking solar arrays and thermal management panels in addition to the highly-dynamic satellite service schedules and rise/set tables. This mission requirement makes the ISS the ideal communications management analogue for future LEO space station and long-duration planetary exploration missions. Future missions, with their precision-pointed, dynamic, laser-based comm links, require complete autonomy for managing high-data rate communications systems. Development of cognitive communications management systems that permit any crew member or payload science specialist, regardless of experience level, to control communications is one of the greater benefits the ISS can offer new space exploration programs. The IAM project met a new mission requirement never previously levied against US space-born communications systems management: process and display the orientation of large solar arrays and thermal control panels based on real-time joint angle telemetry. However, IAM leaves the actual communications availability assessment to human judgement, which introduces unwanted variability because each specialist has a different core of experience with comm link performance. Because the ISS utilizes two different frequency bands, dynamic structure can be occasionally translucent at one frequency while it can completely interdict service at the other frequency. The impact of articulating structure on the comm link can depend on its orientation at the time it impinges on the link. It can become easy for a human specialist to cross-associate experience at one frequency with experience at the other frequency. Additionally, the specialist's experience is incremental, occurring one nine-hour shift at a time. Only the IAM processor experiences the complete 24x7x365 communications link performance for both communications links but, it has no "learning capability." If the IAM processor could be endowed with a cognitive ability to remember past structure-induced comm link outages, based on its knowledge of the ISS position, attitude, communications gear, array joint angles and tracking accuracy, it could convey such experience to the human operator. It could also use its learned communications link behaviors to accurately convey the availability of future communications sessions. Further, the tool could remember how accurately or inaccurately it predicted availability and correct future predictions based on past performance. The IAM tool could learn frequency-specific impacts due to spacecraft structures and pass that information along as "experience." Such development would provide a single artificial intelligence processor that could provide two different experience bases. If it also "knew" the satellite service schedule, it could distinguish structure blockage from schedule or planet blockage and then quickly switch to another satellite. Alternatively, just as a human operator could judge, a cognizant comm system based on the IAM model could "know" that the blockage is not going to last very long and continue tracking a comm satellite, waiting for it to track away from structure. Ultimately, once this capability was fully developed and tested in the Mission Control Center, it could be transferred on-orbit to support development of operations concepts that include more advanced cognitive communications systems. Future applications of this capability are easily foreseen because even more dynamic satellite constellations with more nodes and greater capability are coming. Currently, the ISS fully employs its high-data-rate return link for harvesting payload science. In the coming months, it will double that data rate and is forecast to fully utilize that capability. Already there is talk of an upgrade that quadruples the current data rate allocated to ISS payload science before the end of its mission and laser comm links have already been tested from the ISS. Every data rate upgrade mandates more complicated and sensitive communications equipment which implies greater expertise invested in the human operator. Future on-orbit cognizant comm systems will be needed to meet greater performance demands aboard larger, far more complicated spacecraft. In the LEO environment, the old-style one-satellite-per-spacecraft operations concept will give way to a new concept of a single customer spacecraft simultaneously using multiple comm satellites. Much more highly-dynamic manned LEO missions with decades of crew members potentially increase the demand for communications link performance. A cognizant on-board communications system will meet advanced communications demands from future LEO missions and future planetary missions. The ISS has fledgling components of future exploration programs, both LEO and planetary. Further, the Flight Operations Directorate, through the IAM project, has already begun to develop a communications management system that attempts to solve advanced problems ideally represented by dynamic structure impacting scheduled satellite service. With an earnest project to integrate artificial intelligence into the IAM processor, the ISS Program could develop a cognizant communications system that could be adapted and transferred to future on-orbit avionics designs.
Jackson, Dan↗
The Telesupervised Adaptive Ocean Sensor Fleet (TAOSF) Architecture: Coordination of Multiple Oceanic Robot Boats
Earth science research must bridge the gap between the atmosphere and the ocean to foster understanding of Earth s climate and ecology. Ocean sensing is typically done with satellites, buoys, and crewed research ships. The limitations of these systems include the fact that satellites are often blocked by cloud cover, and buoys and ships have spatial coverage limitations. This paper describes a multi-robot science exploration software architecture and system called the Telesupervised Adaptive Ocean Sensor Fleet (TAOSF). TAOSF supervises and coordinates a group of robotic boats, the OASIS platforms, to enable in-situ study of phenomena in the ocean/atmosphere interface, as well as on the ocean surface and sub-surface. The OASIS platforms are extended deployment autonomous ocean surface vehicles, whose development is funded separately by the National Oceanic and Atmospheric Administration (NOAA). TAOSF allows a human operator to effectively supervise and coordinate multiple robotic assets using a sliding autonomy control architecture, where the operating mode of the vessels ranges from autonomous control to teleoperated human control. TAOSF increases data-gathering effectiveness and science return while reducing demands on scientists for robotic asset tasking, control, and monitoring. The first field application chosen for TAOSF is the characterization of Harmful Algal Blooms (HABs). We discuss the overall TAOSF architecture, describe field tests conducted under controlled conditions using rhodamine dye as a HAB simulant, present initial results from these tests, and outline the next steps in the development of TAOSF.
sensor web↗
Distributed Spacecraft Missions (DSM)
This talk presents the concept of "Distributed Spacecraft Mission (DSM)", its drivers, its challenges and its benefits to NASA future Science and Exploration missions. The presentation focuses on the technology challenges related to DSMs and particularly the needs for Trusted Autonomy and Onboard Processing; particular attention is given to a specific type of DSM, the Intelligent and Collaborative Constellation (ICC). Examples of DSM, ICC and Autonomy-related technologies being currently developed at NASA are being introduced.
Le Moigne, Jacqueline↗
Formal Modeling of Multi-Agent Systems using the Pi-Calculus and Epistemic Logic
Multi-agent systems have become important recently in computer science, especially in artificial intelligence (AI). We allow a broad sense of agent, but require at least that an agent has some measure of autonomy and interacts with other agents via some kind of agent communication language. We are concerned in this paper with formal modeling of multi-agent systems, with emphasis on communication. We propose for this purpose to use the pi-calculus, an extension of the process algebra CCS. Although the literature on the pi-calculus refers to agents, the term is used there in the sense of a process in general. It is our contention, however, that viewing agents in the AI sense as agents in the pi-calculus sense affords significant formal insight. One formalism that has been applied to agents in the AI sense is epistemic logic, the logic of knowledge. The success of epistemic logic in computer science in general has come in large part from its ability to handle concepts of knowledge that apply to groups. We maintain that the pi-calculus affords a natural yet rigorous means by which groups that are significant to epistemic logic may be identified, encapsulated, structured into hierarchies, and restructured in a principled way. This paper is organized as follows: Section 2 introduces the pi-calculus; Section 3 takes a scenario from the classical paper on agent-oriented programming [Sh93] and translates it into a very simple subset of the n-calculus; Section 4 then shows how more sophisticated features of the pi-calculus may bc brought into play; Section 5 discusses how the pi-calculus may be used to define groups for epistemic logic; and Section 6 is the conclusion.
Rorie, Toinette↗
Development of a Ground Test and Analysis Protocol for NASA's NextSTEP Phase 2 Habitation Concepts
The NASA Next Space Technologies for Exploration Partnerships (NextSTEP) program is a public-private partnership model that seeks commercial development of deep space exploration capabilities to support human spaceflight missions around and beyond cislunar space. NASA first issued the Phase 1 NextSTEP Broad Agency Announcement to U.S. industries in 2014, which called for innovative cislunar habitation concepts that leveraged commercialization plans for low-Earth orbit. These habitats will be part of the Deep Space Gateway (DSG), the cislunar space station planned by NASA for construction in the 2020s. In 2016, Phase 2 of the NextSTEP program selected five commercial partners to develop ground prototypes. A team of NASA research engineers and subject matter experts (SMEs) have been tasked with developing the ground-test protocol that will serve as the primary means by which these Phase 2 prototypes will be evaluated. Since 2008, this core test team has successfully conducted multiple spaceflight analog mission evaluations utilizing a consistent set of operational tools, methods, and metrics to enable the iterative development, testing, analysis, and validation of evolving exploration architectures, operations concepts, and vehicle designs. The purpose of implementing a similar evaluation process for the Phase 2 Habitation Concepts is to consistently evaluate different commercial partner ground prototypes to provide data-driven, actionable recommendations for Phase 3. This paper describes the process by which the ground test protocol was developed and the objectives, methods, and metrics by which the NextSTEP Phase 2 Habitation Concepts will be rigorously and systematically evaluated. The protocol has been developed using both a top-down and bottom-up approach. Top-down development began with the Human Exploration and Operations Mission Directorate (HEOMD) exploration objectives and ISS Exploration Capability Study Team (IECST) candidate flight objectives. Strategic questions and associated rationales, derived from these candidate architectural objectives, provide the framework by which the ground-test protocol will address the DSG stack elements and configurations, systems and subsystems, and habitation, science, and EVA functions. From these strategic questions, high-level functional requirements for the DSG were drafted and associated ground-test objectives and analysis protocols were established. Bottom-up development incorporated objectives from NASA SMEs in autonomy, avionics and software, communication, environmental control and life support systems, exercise, extravehicular activity, exploration medical operations, guidance navigation and control, human factors and behavioral performance, human factors and habitability, logistics, Mission Control Center operations, power, radiation, robotics, safety and mission assurance, science, simulation, structures, thermal, trash management, and vehicle health. Top-down and bottom-up objectives were integrated to form overall functional requirements - ground-test objectives and analysis mapping. From this mapping, ground-test objectives were organized into those that will be evaluated through inspection, demonstration, analysis, subsystem standalone testing, and human-in-the-loop (HITL) testing. For the HITL tests, mission-like timelines, procedures, and flight rules have been developed to directly meet ground test objectives and evaluate specific functional requirements. Data collected from these assessments will be analyzed to determine the acceptability of habitation element configurations and the combinations of capabilities that will result in the best habitation platform to be recommended by the test team for Phase 3.
Gernhardt, Michael L.↗
Spacecraft/Rover Hybrids for the Exploration of Small Solar System Bodies: Final Report: NASA NIAC - Phase II Study
This study investigated a mission architecture that allows the systematic and affordable in-situ exploration of small solar system bodies, such as asteroids, comets, and Martian moons (Figure 1). The architecture relies on the novel concept of spacecraft/rover hybrids,which are surface mobility platforms capable of achieving large surface coverage (by attitude controlled hops, akin to spacecraft flight), fine mobility (by tumbling), and coarse instrument pointing (by changing orientation relative to the ground) in the low-gravity environments(micro-g to milli-g) of small bodies. The actuation of the hybrids relies on spinning three internal flywheels. Using a combination of torques, the three flywheel motors can produce a reaction torque in any orientation without additional moving parts. This mobility concept allows all subsystems to be packaged in one sealed enclosure and enables the platforms to be minimalistic. The hybrids would be deployed from a mother spacecraft, which would act as a communication relay to Earth and would aid the in-situ assets with tasks such as localization and navigation (Figure 1). The hybrids are expected to be more capable and affordable than wheeled or legged rovers, due to their multiple modes of mobility (both hopping and tumbling), and have simpler environmental sealing and thermal management (since all components are sealed in one enclosure, assuming non-deployable science instruments). In summary, this NIAC Phase II study has significantly increased the TRL (Technology Readiness Level) of the mobility and autonomy subsystems of spacecraft/rover hybrids, and characterized system engineering aspects in the context of a reference mission to Phobos. Future studies should focus on improving the robustness of the autonomy module and further refine system engineering aspects, in view of opportunities for technology infusion.
mobility platforms↗
An aerobot for global in situ exploration of Titan
This paper describes the design and component testing of an aerobot that would be capable of global in situ exploration of Saturn's moon, Titan, over a 6 to 12 month mission lifetime. The proposed aerobot is a propeller-driven, buoyant vehicle that resembles terrestrial airships. However, the extremely cold Titan environment requires the use of cryogenic materials of construction and careful thermal design for protection of temperature-sensitive payload elements. Multiple candidate balloon materials have been identified based on extensive laboratory testing at 77 K. The most promising materials to date are laminates comprised of polyester fabrics and/or films with areal densities in the range of 40-100 g/m2. The aerobot hull is a streamlined ellipsoid 14 meters in length with a maximum diameter of 3 meters. The enclosed volume of 60 m3 is sufficient to float a mass of 234 kg at a maximum altitude of 8 km at Titan. Forward and aft ballonets are located inside the hull to enable the aerobot to descend to the surface while preserving a fully inflated streamlined shape. Altitude changes are effected primarily through thrust vectoring of the twin main propellers, with pressure modulated buoyancy change via the ballonets available as a slower backup option. A total of 100 W of electrical power is provided to the vehicle by a radioisotope power supply. Up to half of this power is available to the propulsion system to generate a top flight speed in the range of 1-2 m/s. This speed is expected to be greater than the near surface winds at Titan, enabling the aerobot to fly to and hover over targets of interest. A preliminary science payload has been devised for the aerobot to give it the capability for aerial imaging of the surface, atmospheric observations and sampling, and surface sample acquisition and analysis. Targeting, hovering, surface sample acquisition and vehicle health monitoring and automatic safing actions will all require significant on-board autonomy due to the over two hour round trip light time between Titan and Earth. An autonomy architecture and a core set of perception, reasoning and control technologies is under development using a free-flying airship testbed of approximately the same size as the proposed Titan aerobot. Data volume from the Titan science mission is expected to be on the order of 100-300 Mbit per day transmitted either direct to Earth through an 0.8 m high gain antenna or via an orbiter relay using an omni-directional antenna on the aerobot.
mobility↗
Scientific Physical and Operations Characterization (SPOC): Studying Scientists in the Wild to Inform Human Planetary Exploration Operations
The objective of the Scientific Physical and Operational Characterization (SPOC) project is to build an evidence-based description of terrestrial field science to inform the operational, physical, and tool requirements for planetary exploration extravehicular activities (xEVAs). EVAs of the future, including Artemis 2024 and beyond, intend to promote scientific productivity (e.g., LEAG science goals)[1]; however, no clear, objective pathway currently exists to enable this goal, particularly with respect to the desired increase in autonomy imparted to future astronauts. The SPOC project applies expertise in the fields of cognitive systems engineering [2-5], biomechanics, wearable sensors [6-8] and hardware/software to more targetly address these issues. In doing so, a terrestrial fieldwork ground-truth can be established that will benefit human and robotic exploration of other planetary surfaces.
M J Miller↗
Minimizing Operations and Spacecraft Development Costs in a Spacecraft Autonomy Paradigm
Explore the source record for details and available documents.
operations automation cost efficient operations lo↗
Model Based Autonomy for Robust Mars Operations
Space missions have historically relied upon a large ground staff, numbering in the hundreds for complex missions, to maintain routine operations. When an anomaly occurs, this small army of engineers attempts to identify and work around the problem. A piloted Mars mission, with its multiyear duration, cost pressures, half-hour communication delays and two-week blackouts cannot be closely controlled by a battalion of engineers on Earth. Flight crew involvement in routine system operations must also be minimized to maximize science return. It also may be unrealistic to require the crew have the expertise in each mission subsystem needed to diagnose a system failure and effect a timely repair, as engineers did for Apollo 13. Enter model-based autonomy, which allows complex systems to autonomously maintain operation despite failures or anomalous conditions, contributing to safe, robust, and minimally supervised operation of spacecraft, life support, In Situ Resource Utilization (ISRU) and power systems. Autonomous reasoning is central to the approach. A reasoning algorithm uses a logical or mathematical model of a system to infer how to operate the system, diagnose failures and generate appropriate behavior to repair or reconfigure the system in response. The 'plug and play' nature of the models enables low cost development of autonomy for multiple platforms. Declarative, reusable models capture relevant aspects of the behavior of simple devices (e.g. valves or thrusters). Reasoning algorithms combine device models to create a model of the system-wide interactions and behavior of a complex, unique artifact such as a spacecraft. Rather than requiring engineers to all possible interactions and failures at design time or perform analysis during the mission, the reasoning engine generates the appropriate response to the current situation, taking into account its system-wide knowledge, the current state, and even sensor failures or unexpected behavior.
Kurien, James A.↗