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Three Corner Sat (3CS) is a mission of three university nanosatellites scheduled for launch on September 2002. The 3CS misison will utilize significan onboard autonomy to perform onboard science data validation and replanning.
This paper discusses the onboard autonomy software on the Three Corner Sat mission.
In this paper we focus on the use of autonomy to enable and enhance scientific goals for spaceborne missions.
The NASA Johnson Space Center has developed a nanosatellite-class Free Flyer intended for future external inspection and remote viewing of human spacecraft. The Miniature Autonomous Extravehicular Robotic Camera (Mini AERCam) technology demonstration unit has been integrated into the approximate form and function of a flight system. The spherical Mini AERCam Free Flyer is 7.5 inches in diameter and weighs approximately 10 pounds, yet it incorporates significant additional capabilities compared to the 35-pound, 14-inch diameter AERCam Sprint that flew as a Shuttle flight experiment in 1997. Mini AERCam hosts a full suite of miniaturized avionics, instrumentation, communications, navigation, power, propulsion, and imaging subsystems, including digital video cameras and a high resolution still image camera. The vehicle is designed for either remotely piloted operations or supervised autonomous operations, including automatic stationkeeping, point-to-point maneuvering, and waypoint tracking. The Mini AERCam Free Flyer is accompanied by a sophisticated control station for command and control, as well as a docking system for automated deployment, docking, and recharge at a parent spacecraft. Free Flyer functional testing has been conducted successfully on both an airbearing table and in a six-degree-of-freedom closed-loop orbital simulation with avionics hardware in the loop. Mini AERCam aims to provide beneficial on-orbit views that cannot be obtained from fixed cameras, cameras on robotic manipulators, or cameras carried by crewmembers during extravehicular activities (EVA s). On Shuttle or International Space Station (ISS), for example, Mini AERCam could support external robotic operations by supplying orthogonal views to the intravehicular activity (IVA) robotic operator, supply views of EVA operations to IVA and/or ground crews monitoring the EVA, and carry out independent visual inspections of areas of interest around the spacecraft. To enable these future benefits with minimal impact on IVA operators and ground controllers, the Mini AERCam system architecture incorporates intelligent systems attributes that support various autonomous capabilities. 1) A robust command sequencer enables task-level command scripting. Command scripting is employed for operations such as automatic inspection scans over a region of interest, and operator-hands-off automated docking. 2) A system manager built on the same expert-system software as the command sequencer provides detection and smart-response capability for potential system-level anomalies, like loss of communications between the Free Flyer and control station. 3) An AERCam dynamics manager provides nominal and off-nominal management of guidance, navigation, and control (GN&C) functions. It is employed for safe trajectory monitoring, contingency maneuvering, and related roles. This paper will describe these architectural components of Mini AERCam autonomy, as well as the interaction of these elements with a human operator during supervised autonomous control.
Space mission operations are extremely labor and knowledge-intensive and are driven by the ground and flight systems. Inclusion of an autonomy capability can have dramatic effects on mission operations. We describe the past mission operations flow for the Earth Observing-1 (EO-1) spacecraft as well as the more autonomous operations to which we transferred as part of the Autonomous Sciencecraft Experiment (ASE).
We have developed intelligent agent software for onboard system autonomy. Our approach is to provide control agents that automate crew and vehicle systems, and operations assistants that aid humans in working with these autonomous systems. We use the 3 Tier control architecture to develop the control agent software that automates system reconfiguration and routine fault management. We use the Distributed Collaboration and Interaction (DCI) System to develop the operations assistants that provide human services, including situation summarization, event notification, activity management, and support for manual commanding of autonomous system. In this paper we describe how the operations assistants aid situation awareness of the autonomous control agents. We also describe our evaluation of the DCI System to support control engineers during a ground test at Johnson Space Center (JSC) of the Post Processing System (PPS) for regenerative water recovery.
This viewgraph presentation reviews using the Sensor Web capabilities as an enabling technology to allow for progressive autonomy of NASA space missions. The presentation reviews technical challenges for future missions, and some of the capabilities that exist to meet those challenges. To establish the ability of the technology to meet the challenges, experiments were conducted on three missions: Earth Observing 1 (EO-1), Cosmic Hot Interstellar Plasma Spectrometer (CHIPS) and Space Technology 5 (ST-5). These experiments are reviewed.
A lunar outpost will involve a habitat with an integrated set of hardware and software that will maintain a safe environment for human activities. There is a desire for a paradigm shift whereby crew will be the primary mission operators, not ground controllers. There will also be significant periods when the outpost is uncrewed. This will require that significant automation software be resident in the habitat to maintain all system functions and respond to faults. JSC is developing a testbed to allow for early testing and evaluation of different autonomy architectures. This will allow evaluation of different software configurations in order to: 1) understand different operational concepts; 2) assess the impact of failures and perturbations on the system; and 3) mitigate software and hardware integration risks. The testbed will provide an environment in which habitat hardware simulations can interact with autonomous control software. Faults can be injected into the simulations and different mission scenarios can be scripted. The testbed allows for logging, replaying and re-initializing mission scenarios. An initial testbed configuration has been developed by combining an existing life support simulation and an existing simulation of the space station power distribution system. Results from this initial configuration will be presented along with suggested requirements and designs for the incremental development of a more sophisticated lunar habitat testbed.
This viewgraph presentation reviews the work that NASA Goddard Space Flight Center is currently doing and has been involved in in developing onboard autonomy and automation. Emphasis is given to the work being done for the Swift observatory
Task Objectives are: (1) Develop and demonstrate key capabilities for rover long-range science operations using multi-core computing, (a) Adapt three rover technologies to execute on SOA multi-core processor (b) Illustrate performance improvements achieved (c) Demonstrate adapted capabilities with rover hardware, (2) Targeting three high-level autonomy technologies (a) Two for onboard data analysis (b) One for onboard command sequencing/planning, (3) Technologies identified as enabling for future missions, (4)Benefits will be measured along several metrics: (a) Execution time / Power requirements (b) Number of data products processed per unit time (c) Solution quality
The Autonomous Mission Operations project is investigating crew autonomy capabilities and tools for deep space missions. Team members at Ames Research Center, Johnson Space Center and Marshall Space Flight Center are using their experience with ISS Payload operations and TIMELINER to: move earth based command and control assets to on-board for crew access; safely merge core and payload command procedures; give the crew single action intelligent operations; and investigate crew interface requirements.
The purpose of Air Transportation is to move people and cargo safely, efficiently and swiftly to their destinations. The companies and individuals who use aircraft for this purpose, the airspace users, desire to operate their aircraft according to a dynamically optimized business trajectory for their specific mission and operational business model. In current operations, the dynamic optimization of business trajectories is limited by constraints built into operations in the National Airspace System (NAS) for reasons of safety and operational needs of the air navigation service providers. NASA has been developing and testing means to overcome many of these constraints and permit operations to be conducted closer to the airspace user's changing business trajectory as conditions unfold before and during the flight. A roadmap of logical steps progressing toward increased user autonomy is proposed, beginning with NASA's Traffic Aware Strategic Aircrew Requests (TASAR) concept that enables flight crews to make informed, deconflicted flight-optimization requests to air traffic control. These steps include the use of data communications for route change requests and approvals, integration with time-based arrival flow management processes under development by the Federal Aviation Administration (FAA), increased user authority for defining and modifying downstream, strategic portions of the trajectory, and ultimately application of self-separation. This progression takes advantage of existing FAA NextGen programs and RTCA standards development, and it is designed to minimize the number of hardware upgrades required of airspace users to take advantage of these advanced capabilities to achieve dynamically optimized business trajectories in NAS operations. The roadmap is designed to provide operational benefits to first adopters so that investment decisions do not depend upon a large segment of the user community becoming equipped before benefits can be realized. The issues of equipment certification and operational approval of new procedures are addressed in a way that minimizes their impact on the transition by deferring a change in the assignment of separation responsibility until a large body of operational data is available to support the safety case for this change in the last roadmap step.This paper will relate the roadmap steps to ongoing activities to clarify the economics-based transition to these technologies for operational use.
This presentation describes the development and demonstration of human autonomy teaming technologies for improving aviation safety and efficiency during nominal and off-nominal operations by developing and validating increasingly autonomous systems concepts, technologies, and procedures.
Flights at low altitudes in close proximity to electrical transmission infrastructure present serious navigational challenges: GPS and radio communication quality is variable and yet tight position control is needed to measure defects while avoiding collisions with ground structures. To advance unmanned aerial vehicle (UAV) navigation technology while accomplishing a task with economic and societal benefit, a high voltage electrical infrastructure inspection reference mission was designed. An integrated air-ground platform was developed for this mission and tested in two days of experimental flights to determine whether navigational augmentation was needed to successfully conduct a controlled inspection experiment. The airborne component of the platform was a multirotor UAV built from commercial off-the-shelf hardware and software, and the ground component was a commercial laptop running open source software. A compact ultraviolet sensor mounted on the UAV can locate 'hot spots' (potential failure points in the electric grid), so long as the UAV flight path adequately samples the airspace near the power grid structures. To improve navigation, the platform was supplemented with two navigation technologies: lidar-to-polyhedron preflight processing for obstacle demarcation and inspection distance planning, and trajectory management software to enforce inspection standoff distance. Both navigation technologies were essential to obtaining useful results from the hot spot sensor in this obstacle-rich, low-altitude airspace. Because the electrical grid extends into crowded airspaces, the UAV position was tracked with NASA unmanned aerial system traffic management (UTM) technology. The following results were obtained: (1) Inspection of high-voltage electrical transmission infrastructure to locate 'hot spots' of ultraviolet emission requires navigation methods that are not broadly available and are not needed at higher altitude flights above ground structures. (2) The sensing capability of a novel airborne UV detector was verified with a standard ground-based instrument. Flights with this sensor showed that UAV measurement operations and recording methods are viable. With improved sensor range, UAVs equipped with compact UV sensors could serve as the detection elements in a self-diagnosing power grid. (3) Simplification of rich lidar maps to polyhedral obstacle maps reduces data volume by orders of magnitude, so that computation with the resultant maps in real time is possible. This enables real-time obstacle avoidance autonomy. Stable navigation may be feasible in the GPS-deprived environment near transmission lines by a UAV that senses ground structures and compares them to these simplified maps. (4) A new, formally verified path conformance software system that runs onboard a UAV was demonstrated in flight for the first time. It successfully maneuvered the aircraft after a sudden lateral perturbation that models a gust of wind, and processed lidar-derived polyhedral obstacle maps in real time. (5) Tracking of the UAV in the national airspace using the NASA UTM technology was a key safety component of this reference mission, since the flights were conducted beneath the landing approach to a heavily used runway. Comparison to autopilot tracking showed that UTM tracking accurately records the UAV position throughout the flight path.
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).
This presentation discusses high-level capabilities and interests in autonomy at NASA Ames, and describes some methods for collaboration.
NASA's work in deploying autonomy technologies to improve aeronautics and space missions over the last 25 years. Widely disseminated examples are highlighted, mostly in a few timeline charts, but with a few specific examples.
NASA has been exploring the use of artificial intelligence technologies to improve vehicle and airspace capabilities for over 20 years. This research has ranged from the use of neural nets to allow adaptive control, to autonomous rotorcraft operations, to real-time prognostics, to an eventual goal of autonomous vehicles operating in an autonomous airspace, in the context of smart communities. Examples of past research and future directions in autonomy for aeronautics will be presented.