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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 181 records · Page 10

Relative Navigation for Spacecraft Formation Flying

The Goddard Space Flight Center Guidance, Navigation, and Control Center (GNCC) is currently developing and implementing advanced satellite systems to provide autonomous control of formation flyers. The initial formation maintenance capability will be flight-demonstrated on the Earth-Orbiter-1 (EO-l) satellite, which is planned under the National Aeronautics and Space Administration New Millennium Program to be a coflight with the Landsat-7 (L-7) satellite. Formation flying imposes relative navigation accuracy requirements in addition to the orbit accuracy requirements for the individual satellites. In the case of EO-1 and L-7, the two satellites are in nearly coplanar orbits, with a small difference in the longitude of the ascending node to compensate for the Earth's rotation. The GNCC has performed trajectory error analysis for the relative navigation of the EO-1/L-7 formation, as well as for a more advanced tracking configuration using cross- link satellite communications. This paper discusses the orbit determination and prediction accuracy achievable for EO-1 and L-7 under various tracking and orbit determination scenarios and discusses the expected relative separation errors in their formation flying configuration.

Hartman, Kate R.↗

Autonomous Systems, Robotics, and Computing Systems Capability Roadmap: NRC Dialogue

Contents include the following: Introduction. Process, Mission Drivers, Deliverables, and Interfaces. Autonomy. Crew-Centered and Remote Operations. Integrated Systems Health Management. Autonomous Vehicle Control. Autonomous Process Control. Robotics. Robotics for Solar System Exploration. Robotics for Lunar and Planetary Habitation. Robotics for In-Space Operations. Computing Systems. Conclusion.

Zornetzer, Steve↗

An autonomous fault detection, isolation, and recovery system for a 20-kHz electric power distribution test bed

Future space explorations will require long term human presence in space. Space environments that provide working and living quarters for manned missions are becoming increasingly larger and more sophisticated. Monitor and control of the space environment subsystems by expert system software, which emulate human reasoning processes, could maintain the health of the subsystems and help reduce the human workload. The autonomous power expert (APEX) system was developed to emulate a human expert's reasoning processes used to diagnose fault conditions in the domain of space power distribution. APEX is a fault detection, isolation, and recovery (FDIR) system, capable of autonomous monitoring and control of the power distribution system. APEX consists of a knowledge base, a data base, an inference engine, and various support and interface software. APEX provides the user with an easy-to-use interactive interface. When a fault is detected, APEX will inform the user of the detection. The user can direct APEX to isolate the probable cause of the fault. Once a fault has been isolated, the user can ask APEX to justify its fault isolation and to recommend actions to correct the fault. APEX implementation and capabilities are discussed.

Quinn, Todd M.↗

Knowledge-based Autonomous Test Engineer (KATE)

Mathematical models of system components have long been used to allow simulators to predict system behavior to various stimuli. Recent efforts to monitor, diagnose, and control real-time systems using component models have experienced similar success. NASA Kennedy is continuing the development of a tool for implementing real-time knowledge-based diagnostic and control systems called KATE (Knowledge based Autonomous Test Engineer). KATE is a model-based reasoning shell designed to provide autonomous control, monitoring, fault detection, and diagnostics for complex engineering systems by applying its reasoning techniques to an exchangeable quantitative model describing the structure and function of the various system components and their systemic behavior.

Parrish, Carrie L.↗

Bilevel shared control for teleoperators

A shared system is disclosed for robot control including integration of the human and autonomous input modalities for an improved control. Autonomously planned motion trajectories are modified by a teleoperator to track unmodelled target motions, while nominal teleoperator motions are modified through compliance to accommodate geometric errors autonomously in the latter. A hierarchical shared system intelligently shares control over a remote robot between the autonomous and teleoperative portions of an overall control system. Architecture is hierarchical, and consists of two levels. The top level represents the task level, while the bottom, the execution level. In space applications, the performance of pure teleoperation systems depend significantly on the communication time delays between the local and the remote sites. Selection/mixing matrices are provided with entries which reflect how each input's signals modality is weighted. The shared control minimizes the detrimental effects caused by these time delays between earth and space.

Hayati, Samad A.↗

A Prototype System for Ground Control Space Telerobotics

A telerobotics system is described which provides supervised autonomous control capability for time-delayed ground-remote control applications. The system includes a local site operator interface for interactive task description and a remote site task execution system. Interactive stereo graphics overlay on video is provided at the local site to update the remote environmental model. The remote site system is capable of nominal task execution as well as monitoring and reflex action. Execution utilizes multiple control modules which execute based upon command parameterization.

robotics autonomous control telerobotics manipulat↗

Autonomous power expert fault diagnostic system for Space Station Freedom electrical power system testbed

The goal of the Autonomous Power System (APS) program is to develop and apply intelligent problem solving and control to the Space Station Freedom Electrical Power System (SSF/EPS) testbed being developed and demonstrated at NASA Lewis Research Center. The objectives of the program are to establish artificial intelligence technology paths, to craft knowledge-based tools with advanced human-operator interfaces for power systems, and to interface and integrate knowledge-based systems with conventional controllers. The Autonomous Power EXpert (APEX) portion of the APS program will integrate a knowledge-based fault diagnostic system and a power resource planner-scheduler. Then APEX will interface on-line with the SSF/EPS testbed and its Power Management Controller (PMC). The key tasks include establishing knowledge bases for system diagnostics, fault detection and isolation analysis, on-line information accessing through PMC, enhanced data management, and multiple-level, object-oriented operator displays. The first prototype of the diagnostic expert system for fault detection and isolation has been developed. The knowledge bases and the rule-based model that were developed for the Power Distribution Control Unit subsystem of the SSF/EPS testbed are described. A corresponding troubleshooting technique is also described.

Truong, Long V.↗

Autonomous Spacecraft Communication Interface for Load Planning

Ground-based controllers can remain in continuous communication with spacecraft in low Earth orbit (LEO) with near-instantaneous communication speeds. This permits near real-time control of all of the core spacecraft systems by ground personnel. However, as NASA missions move beyond LEO, light-time communication delay issues, such as time lag and low bandwidth, will prohibit this type of operation. As missions become more distant, autonomous control of manned spacecraft will be required. The focus of this paper is the power subsystem. For present missions, controllers on the ground develop a complete schedule of power usage for all spacecraft components. This paper presents work currently underway at NASA to develop an architecture for an autonomous spacecraft, and focuses on the development of communication between the Mission Manager and the Autonomous Power Controller. These two systems must work together in order to plan future load use and respond to unanticipated plan deviations. Using a nominal spacecraft architecture and prototype versions of these two key components, a number of simulations are run under a variety of operational conditions, enabling development of content and format of the messages necessary to achieve the desired goals. The goals include negotiation of a load schedule that meets the global requirements (contained in the Mission Manager) and local power system requirements (contained in the Autonomous Power Controller), and communication of off-plan disturbances that arise while executing a negotiated plan. The message content is developed in two steps: first, a set of rapid-prototyping "paper" simulations are preformed; then the resultant optimized messages are codified for computer communication for use in automated testing.

Controls↗

Towards autonomous fuzzy control

The efficient implementation of on-line adaptation in real time is an important research problem in fuzzy control. The goal is to develop autonomous self-organizing controllers employing system-independent control meta-knowledge which enables them to adjust their control policies depending on the systems they control and the environments in which they operate. An autonomous fuzzy controller would continuously observe system behavior while implementing its control actions and would use the outcomes of these actions to refine its control policy. It could be designed to lie dormant when its control actions give rise to adequate performance characteristics but could rapidly and autonomously initiate real-time adaptation whenever its performance degrades. Such an autonomous fuzzy controller would have immense practical value. It could accommodate individual variations in system characteristics and also compensate for degradations in system characteristics caused by wear and tear. It could also potentially deal with black-box systems and control scenarios. On-going research in autonomous fuzzy control is reported. The ultimate research objective is to develop robust and relatively inexpensive autonomous fuzzy control hardware suitable for use in real time environments.

Shenoi, Sujeet↗

Design of a wheeled articulating land rover

The WALRUS is a wheeled articulating land rover that will provide Ames Research Center with a reliable, autonomous vehicle for demonstrating and evaluating advanced technologies. The vehicle is one component of the Ames Research Center's on-going Human Exploration Demonstration Project. Ames Research Center requested a system capable of traversing a broad spectrum of surface types and obstacles. In addition, this vehicle must have an autonomous navigation and control system on board and its own source of power. The resulting design is a rover that articulates in two planes of motion to allow for increased mobility and stability. The rover is driven by six conical shaped aluminum wheels, each with an independent, internally coupled motor. Mounted on the rover are two housings and a removable remote control system. In the housings, the motor controller board, tilt sensor, navigation circuitry, and QED board are mounted. Finally, the rover's motors and electronics are powered by thirty C-cell rechargeable batteries, which are located in the rover wheels and recharged by a specially designed battery charger.

Stauffer, Larry↗

Explanation Constraint Programming for Model-based Diagnosis of Engineered Systems

We can expect to see an increase in the deployment of unmanned air and land vehicles for autonomous exploration of space. In order to maintain autonomous control of such systems, it is essential to track the current state of the system. When the system includes safety-critical components, failures or faults in the system must be diagnosed as quickly as possible, and their effects compensated for so that control and safety are maintained under a variety of fault conditions. The Livingstone fault diagnosis and recovery kernel and its temporal extension L2 are examples of model-based reasoning engines for health management. Livingstone has been shown to be effective, it is in demand, and it is being further developed. It was part of the successful Remote Agent demonstration on Deep Space One in 1999. It has been and is being utilized by several projects involving groups from various NASA centers, including the In Situ Propellant Production (ISPP) simulation at Kennedy Space Center, the X-34 and X-37 experimental reusable launch vehicle missions, Techsat-21, and advanced life support projects. Model-based and consistency-based diagnostic systems like Livingstone work only with discrete and finite domain models. When quantitative and continuous behaviors are involved, these are abstracted to discrete form using some mapping. This mapping from the quantitative domain to the qualitative domain is sometimes very involved and requires the design of highly sophisticated and complex monitors. We propose a diagnostic methodology that deals directly with quantitative models and behaviors, thereby mitigating the need for these sophisticated mappings. Our work brings together ideas from model-based diagnosis systems like Livingstone and concurrent constraint programming concepts. The system uses explanations derived from the propagation of quantitative constraints to generate conflicts. Fast conflict generation algorithms are used to generate and maintain multiple candidates whose consistency can be tracked across multiple time steps.

Narasimhan, Sriram↗

Supervised autonomous control, shared control, and teleoperation for space servicing

A local-remote telerobot system for single- and dual-arm supervised autonomy, shared control, and teleoperation has been demonstrated. The system is composed of two distinct parts: the local site, where the operator resides; and the remote site, where the robots reside. The system could be further separated into dual local sites communicating with a common remote site. This is valuable for potential space missions where a space based robotic system may be controlled either by a space based operator or by a ground based operator. Also, multiple modes of control integrated into a common system are valuable for satisfying different servicing scenarios. The remote site single arm control system is described, and its parameterization for different supervised autonomous control, shared control, and teleoperation tasks are given. Experimental results are also given for selected tasks. The tasks include compliant grasping, orbital replacement unit changeout, bolt seating and turning, electronics card removal and insertion, and door opening.

Backes, Paul G.↗

Design, Development and Testing of the Miniature Autonomous Extravehicular Robotic Camera (Mini AERCam) Guidance, Navigation and Control System

Engineers at NASA Johnson Space Center have designed, developed, and tested a nanosatellite-class free-flyer intended for future external inspection and remote viewing of human spaceflight activities. The technology demonstration system, known as the Miniature Autonomous Extravehicular Robotic Camera (Mini AERCam), has been integrated into the approximate form and function of a flight system. The primary focus has been to develop a system capable of providing external views of the International Space Station. The Mini AERCam system is spherical-shaped and less than eight inches in diameter. It has a full suite of guidance, navigation, and control hardware and software, and is equipped with two digital video cameras and a high resolution still image camera. The vehicle is designed for either remotely piloted operations or supervised autonomous operations. Tests have been performed in both a six degree-of-freedom closed-loop orbital simulation and on an air-bearing table. The Mini AERCam system can also be used as a test platform for evaluating algorithms and relative navigation for autonomous proximity operations and docking around the Space Shuttle Orbiter or the ISS.

Wagenknecht, J.↗

Prognostics As-A-Service: A Scalable Cloud Architecture for Prognostics

Comprehensive aircraft system health-state awareness is critical for maintaining safe, efficient growth in global operations, enabling higher levels of autonomy, and facilitating new forms of aviation. Maintainers, vehicle operators, air traffic controllers, dispatchers, pilots, autonomous systems, and other decision-makers must have reliable real-time knowledge of the vehicle health, the health of its critical composite systems, predictions of how health changes with time, and forecasts of how its capabilities change with health degradation to preserve safety and efficiency. Providing this information in a reliable manner in computationally constrained environments and across a wide range of vehicles and systems continues to be a challenge. This challenge can be partially resolved through cloud computing, where the execution of prognostic and diagnostic algorithms is performed on a network of remote servers hosted on the internet. NASA is developing a cloud computing service, Prognostics As-A-Service (PaaS), that explores the feasibility and challenges of cloud-enhanced prognostics. Though such a system has broad applicability, this research effort is focused on aviation applications.

Prognostics↗