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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

A Decision-Theoretic Approach to Autonomous Planetary Rover Control

The report discusses the: Decentralized Control of Markov Decision Processes. Study the complexity of decentralized control of Markov decision processes, and develop algorithms for finding optimal control policies. Scheduling Contract Algorithms. Develop an optimal method for scheduling runs of a contract anytime algorithm (one that takes the deadline as input) in situations where the deadline is unknown, multiple problem instances must be solved, and a multi-processor machine is available. Planetary Rover Control as a Markov Decision Process.Use the Markov decision process framework to formalize and solve problems in planetary rover control. Adaptive Peer Selection. Use reinforcement learning to maximize the expected down-load speed for a client in a peer-to-peer file sharing system.

Zilberstein, Shlomo↗
NASA NTRS2001

Background and architecture for an autonomous ground station controller

The Deep Space Station Controller (DSSC) is state of the art ground station control architecture being developed at JPL. During the past few years the technology development program at JPL demonstrated a series of increasingly competent automated ground station prototypes of which the DSSC is the latest. It has been designed for robust closed loop control of ground stations utilized for forward and return link communications with NASA's deep space exploration missions.

controller for ground station automation fault det↗
NASA NTRS2008

Guidance and control for an autonomous soaring UAV

The present invention provides a practical method for UAVs to take advantage of thermals in a manner similar to piloted aircrafts and soaring birds. In general, the invention is a method for a UAV to autonomously locate a thermal and be guided to the thermal to greatly improve range and endurance of the aircraft.

Allen, Michael J.↗
NASA NTRSDate not supplied

Autonomous Spacecraft Attitude Control Using Deep Reinforcement Learning

While machine learning and spacecraft autonomy continue to gain research interest, significant work remains to be done in efficiently applying modern machine learning techniques to problems in space ight. This study presents a framework for deriving a discrete neural spacecraft attitude controller using reinforcement learning, a paradigm of machine learning, without the need for high-performance computing. The developed attitude controller is an approximately time-optimal solution to a highly constrained control problem, able to achieve well above industry-standard pointing accuracies. Control examples are also presented of the agent performing large-angle spacecraft slews in the developed simulation environment and future extensions of this work are discussed.

ATAP↗
NASA NTRS1999

Advanced Design and Implementation of a Control Architecture for Long Range Autonomous Planetary Rovers

An advanced design and implementation of a Control Architecture for Long Range Autonomous Planetary Rovers is presented using a hierarchical top-down task decomposition, and the common structure of each design is presented based on feedback control theory. Graphical programming is presented as a common intuitive language for the design when a large design team is composed of managers, architecture designers, engineers, programmers, and maintenance personnel. The whole design of the control architecture consists in the classic control concepts of cyclic data processing and event-driven reaction to achieve all the reasoning and behaviors needed. For this purpose, a commercial graphical tool is presented that includes the mentioned control capabilities. Messages queues are used for inter-communication among control functions, allowing Artificial Intelligence (AI) reasoning techniques based on queue manipulation. Experimental results show a highly autonomous control system running in real time on top the JPL micro-rover Rocky 7 controlling simultaneously several robotic devices. This paper validates the sinergy between Artificial Intelligence and classic control concepts in having in advanced Control Architecture for Long Range Autonomous Planetary Rovers.

Martin-Alvarez, A.↗
NASA NTRS1999

Cardiovascular Session Summary

It was apparent that the bed-rest and spaceflight data indicated that decreases in plasma volume and cardiac atrophy along with cardiac remodeling were fundamental changes which predisposed many astronauts to post flight orthostatic intolerance. Despite the recently acquired in-flight and post-flight muscle sympathetic nerve activity findings suggesting that the sympathetic nerve responses were appropriate there remains significant contrary data from bed-rest studies, post- flight stand tests and hind-limb unweighted rat studies that suggest that the vasoconstrictive responses were compromised at least insufficient in susceptible individuals. The key issues raised is whether a diminished increase in sympathetic activity from baseline without changes in 254 First Biennial Space Biomedical Investigators'Workshop Cardiovascular peak response or receptor adaptations is an abnormal response or is an individual variance of response to the accentuated decrease in stroke volume. Data relating autonomic neural control of heart rate were presented to suggest that the vagal and sympathetic control of heart rate was attenuated. Also, bed-rest and space flight induced attenuated baroreflex control of heart rate was shown to be restored to pre-bedrest function by one bout of maximal dynamic exercise. However, these data were confounded by relying on the use of R-R interval as a measure of efferent responses of the baroreflex during a condition in which the baseline heart rate was changed. Clearly the idea that the autonomic control of heart rate may be changed by microgravity needs further investigation. This direction is suggested despite the fact that in the triple product (HR x SV x TPR = MAP) assessment of the regulation of arterial blood pressure during orthostasis the role of the HR reflex may be less influential than that associated. with cardiac atrophy (SV changes) and aberrant sympathetic vasoconstriction (resistance) changes. Although sympathetic nerve activity responses in-flight and post-flight on neurolab appeared appropriate, enough bed-rest and post-flight stand test data, along with animal model data suggest that vasoconstriction was compromised. The mechanism of this compromised vasoconstriction needs to be delineated. Other major findings concerning microgravity and physiological regulatory systems are that: I . Thermoregulatory adaptation appear to suggest some decrements in the control of cutaneous vasodilation and sweating; 2. Calcium resorption and dietary calcium need to be defined for differing durations of spaceflight, especially as the effects of excess calcium on vasomotor function appears to be detrimental; 3. Neurohumoral mechanisms of microgravity induced changes in neural function and the regulation of plasma volume and total body water, bone resorption and autonomic neural control of the circulation need further delineation; 4. As performance of work tasks become prolonged, the mechanisms of blood pressure regulation in microgravity needs to be used in the recovery period from prolonged work tasks.

Raven, Peter↗
NASA NTRS2017

Autonomous Guidance Navigation and Control for Agile Quadrotors Using Polynomial Trajectory Planning and L1 Adaptive Control

We address the challenge to allow efficient autonomous flight in real world environments, both indoor and outdoor. We use a straight-line SE-SCP (Spherical Expansion and Sequential Convex Programming) [algorithm] to find an initial route through the environment and minimum snap trajectory generation using piecewise polynomials. Then, we implement an adaptive robust control able to address some robustness issues for quadrotors in outdoor flight, such as mass variation and wind disturbances. Coupling these techniques we allow high-speed and aggressive autonomous flight through obstacle-dense indoor environments, as well as address outdoor disturbances.

Landolfi, Mattia↗
NASA NTRSDate not supplied

Autonomous Navigation, Guidance, and Control Software in a Low SWaP Box

Onboard autonomy is a necessity for responsive space operations. Autonomous navigation, guidance, and control (NGC) enables space missions to reduce their dependence on high demand ground assets and costly ground personnel. It also allows for in-situ decision making and higher return on mission data. A flight software and hardware system providing this capability, called “autoNGC,” is currently being developed at NASA Goddard Space Flight Center for infusion into multiple future missions. The autoNGC flight software is built on the plug-and-play architecture of the core Flight System (cFS) consisting of the standard cFS apps and newly developed autoNGC interface apps and libraries. The various apps cooperate through communication over the message-based software bus. With the plug-and-play architecture of autoNGC, cFS apps can easily be added and replaced to meet the needs of different missions, even after launch. The first flight software release of autoNGC is targeted for Summer 2024 to provide autonomous navigation at the Moon and beyond. It can perform sensor fusion of multiple measurement types including pseudo-range from a Global Navigation Satellite System (GNSS) receiver (including weak signal), 1-way and 2-way range and Doppler from ground stations (i.e., direct to Earth (DTE)), bearing and range from optical camera images, and accelerometer data. Accurate onboard navigation and timing is obtained through the Goddard Enhanced Onboard Navigation System (GEONS) software library which fuses different measurement types through an extended Kalman filter (EKF) framework. Optical measurements that are ingested in GEONS are first extracted from optical images by the cFS Goddard Image Analysis and Navigation Tool (cGIANT) app. If the imaged body is far enough away that it appears as a pixel or cluster of pixels, then bearing angles to the body centroid can be provided. If the body is close enough and the shape is known coarsely, then bearing angles and range to the body centroid can be derived from the limb. Bearing angles to individual surface features can also be extracted (i.e., terrain relative navigation (TRN)). Onboard guidance and control capabilities are being developed for a future release to perform autonomous station-keeping and trajectory correction maneuvers in multiple orbital regimes. Capabilities to enable distributed systems missions and constellations, such as crosslink measurements, and onboard time management are being developed as well. The first hardware implementation of autoNGC is a minimal size, weight, and power (SWaP) design allowing for inclusion into CubeSats and SmallSat-size buses. Advancements in miniaturized space processors, such as the SpaceCube 3.0 Mini and the SpaceCube Mini-Z are utilized for low SWaP while maintaining a high level of performance. The current enclosure design is 12 cm x 17 cm x 13.5 cm. The box mass is expected to be less than 2 kg, and the nominal power is 21 W. In order to accommodate a wide range of missions, the hardware interfaces are designed for flexibility with a variety of sensor inputs. Through comprehensive testing in the software-in-the-loop, processor-in-the-loop, and hardware-in-the-loop test beds that are concurrently being developed, autoNGC is expected to achieve TRL 6 by late 2024.

Sun Hur-Diaz↗
NASA NTRS2012

On Optimal Control of Non-Autonomous Switched Systems with a Fixed Mode Sequence

We consider differentiability with respect to the switch times of the value function of an optimal control problem for a non-autonomous switched system. The control variables are the switch times between the modes and the input in each mode. We provide a method to compute the derivative of the cost function given a nominal input. Then, we view the optimal control problem as a parametrized optimization problem in which the switch times are the parameters and the optimization is over the set of feasible inputs of each mode. From this point of view, we provide conditions under which the continuity and differentiability of the optimal value function, that is the cost function optimized over the inputs, can be guaranteed.

Kamgarpour, Maryam↗
NASA NTRS2017

Modular Autonomous Systems Technology Framework: A Distributed Solution for System Monitoring and Control

The Modular Autonomous Systems Technology (MAST) framework is a tool for building distributed, hierarchical autonomous systems. Originally intended for the autonomous monitoring and control of spacecraft, this framework concept provides support for variable autonomy, assume-guarantee contracts, and efficient communication between subsystems and a centralized systems manager. MAST was developed at NASA's Johnson Space Center (JSC) and has been applied to an integrated spacecraft example scenario.

Badger, Julia M.↗