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At least 451 records · Page 25

Case Study: Test Results of a Tool and Method for In-Flight, Adaptive Control System Verification on a NASA F-15 Flight Research Aircraft

Adaptive control technologies that incorporate learning algorithms have been proposed to enable autonomous flight control and to maintain vehicle performance in the face of unknown, changing, or poorly defined operating environments [1-2]. At the present time, however, it is unknown how adaptive algorithms can be routinely verified, validated, and certified for use in safety-critical applications. Rigorous methods for adaptive software verification end validation must be developed to ensure that. the control software functions as required and is highly safe and reliable. A large gap appears to exist between the point at which control system designers feel the verification process is complete, and when FAA certification officials agree it is complete. Certification of adaptive flight control software verification is complicated by the use of learning algorithms (e.g., neural networks) and degrees of system non-determinism. Of course, analytical efforts must be made in the verification process to place guarantees on learning algorithm stability, rate of convergence, and convergence accuracy. However, to satisfy FAA certification requirements, it must be demonstrated that the adaptive flight control system is also able to fail and still allow the aircraft to be flown safely or to land, while at the same time providing a means of crew notification of the (impending) failure. It was for this purpose that the NASA Ames Confidence Tool was developed [3]. This paper presents the Confidence Tool as a means of providing in-flight software assurance monitoring of an adaptive flight control system. The paper will present the data obtained from flight testing the tool on a specially modified F-15 aircraft designed to simulate loss of flight control faces.

Jacklin, Stephen A.↗

Search Problems in Mission Planning and Navigation of Autonomous Aircraft

An architecture for the control of an autonomous aircraft is presented. The architecture is a hierarchical system representing an anthropomorphic breakdown of the control problem into planner, navigator, and pilot systems. The planner system determines high level global plans from overall mission objectives. This abstract mission planning is investigated by focusing on the Traveling Salesman Problem with variations on local and global constraints. Tree search techniques are applied including the breadth first, depth first, and best first algorithms. The minimum-column and row entries for the Traveling Salesman Problem cost matrix provides a powerful heuristic to guide these search techniques. Mission planning subgoals are directed from the planner to the navigator for planning routes in mountainous terrain with threats. Terrain/threat information is abstracted into a graph of possible paths for which graph searches are performed. It is shown that paths can be well represented by a search graph based on the Voronoi diagram of points representing the vertices of mountain boundaries. A comparison of Dijkstra's dynamic programming algorithm and the A* graph search algorithm from artificial intelligence/operations research is performed for several navigation path planning examples. These examples illustrate paths that minimize a combination of distance and exposure to threats. Finally, the pilot system synthesizes the flight trajectory by creating the control commands to fly the aircraft.

Krozel, James A.↗

Model-based Executive Control through Reactive Planning for Autonomous Rovers

This paper reports on the design and implementation of a real-time executive for a mobile rover that uses a model-based, declarative approach. The control system is based on the Intelligent Distributed Execution Architecture (IDEA), an approach to planning and execution that provides a unified representational and computational framework for an autonomous agent. The basic hypothesis of IDEA is that a large control system can be structured as a collection of interacting agents, each with the same fundamental structure. We show that planning and real-time response are compatible if the executive minimizes the size of the planning problem. We detail the implementation of this approach on an exploration rover (Gromit an RWI ATRV Junior at NASA Ames) presenting different IDEA controllers of the same domain and comparing them with more classical approaches. We demonstrate that the approach is scalable to complex coordination of functional modules needed for autonomous navigation and exploration.

Finzi, Alberto↗

Lunabotics Mining Competition: Inspiration through Accomplishment

Space Mining for resources such as water ice, and regolith, which contain many elements in the form of metals, minerals, volatiles and other compounds, is a necessary step in Space Resource Utilization. One of the primary goals is to extract propellants from the regolith such as oxygen and hydrogen which could then be used for in-space transportation. In addition, the space mining system can be used for various construction tasks that can benefit human and robotic exploration as well as scientific investigations based on the exposed topography. The National Aeronautics & Space Administration (NASA) Lunabotics Mining Competition is a university-level competition designed to engage and retain students in science, technology, engineering and mathematics (STEM). NASA will directly benefit from the competition by encouraging the development of innovative lunar excavation concepts from universities which may result in clever ideas and solutions which could be applied to an actual lunar excavation device or payload. The challenge is for students to design and build a remote controlled or autonomous excavator, called a lunabot, that can collect and deposit a minimum of 10 kilograms of lunar simulant within 15 minutes. The complexities of the challenge include the abrasive characteristics of the lunar simulant, the weight and size limitations of the lunabot, and the ability to control the lunabot from a remote control center or operate autonomously. This paper will present an update of the results and lessons learned during the first and second annual Lunabotics Mining Competitions held in May 2010 and May 2011. It will also preview the 2012 competition with a review of the revised rules. In 2010,22 United States (US) universities competed, and in May 2011 the competition was opened to international participation. In 2011, 36 teams actually competed from 26 USA states and 4 foreign countries (India, Bangladesh, Colombia and Canada). This combined total directly inspired an estimated 653 university students. In 2012 more students and the public will be engaged via internet broadcasting and social networking media. The various designs will be cataloged and categorized to provide information to future Lunabotics mining robot designers and competitors. It is also expected to be of value for actual future space missions, as knowledge is gained from testing many innovative prototypes in simulated lunar regolith.

Mueller, Robert P.↗

Cardiovascular response to lower body negative pressure stimulation before, during, and after space flight

BACKGROUND: It is well known that space travel cause post-flight orthostatic hypotension and it was assumed that autonomic cardiovascular control deteriorates in space. Lower body negative pressure (LBNP) was used to assess autonomic function of the cardiovascular system. METHODS: LBNP tests were performed on six crew-members before and on the first days post-flight in a series of three space missions. Additionally, two of the subjects performed LBNP tests in-flight. LBNP mimics fluid distribution of upright posture in a gravity independent way. It causes an artificial sequestration of blood, reduces preload, and filtrates plasma into the lower part of the body. Fluid distribution was assessed by bioelectrical impedance and anthropometric measurements. RESULTS: Heart rate, blood pressure, and total peripheral resistance increased significantly during LBNP experiments in-flight. The decrease in stroke volume, the increased pooling of blood, and the increased filtration of plasma into the lower limbs during LBNP indicated that a plasma volume reduction and a deficit of the interstitial volume of lower limbs rather than a change in cardiovascular control was responsible for the in-flight response. Post-flight LBNP showed no signs of cardiovascular deterioration. The still more pronounced haemodynamic changes during LBNP reflected the expected behaviour of cardiovascular control faced with less intravascular volume. In-flight, the status of an intra-and extravascular fluid deficit increases sympathetic activity, the release of vasoactive substances and consequently blood pressure. Post-flight, blood pressure decreases significantly below pre-flight values after restoration of volume deficits. CONCLUSION: We conclude that the cardiovascular changes in-flight are a consequence of a fluid deficit rather than a consequence of changes in autonomic signal processing.

manned↗

Self-Aware Local Autonomous and Semi-Cooperative Control for Cross-Layered Resilience (SLAC3R)

The objective of this work is to develop and demonstrate novel, adaptive, lightweight algorithms that enable the decision-making agents in a large cyber-physical network to act both autonomously and in collaborative harmony to enforce assured resilience across spatiotemporal layers, even under unforeseen adversarial scenarios (e.g., high- impact-low-probability events). Towards this end, the proposed solution will serve as minimally invasive add-on layers that bridge the existing (faster, reactive) local myopic controls and (slower, predictive) centralized optimization. Importantly, the proposed algorithms will enable the multi-agent network to autonomously and collaboratively enforce resilient operation under no or limited communication environment typical of severe cyber- physical adversarial events. The expected outcome of this effort is a suite of prototype, open-source, software algorithms for safety-aware local autonomous and semi-cooperative control (SLAC3R), demonstrated on networked microgrids (via RD2C/Thrust-1 OPAL-RT testbed).

97 MATHEMATICS AND COMPUTING↗

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.↗

Command and telemetry in autonomous spacecraft design

Some major steps are summarized in the evolution of autonomous design features for planetary exploration spacecraft. The control and data architectures for the Viking, Voyager, and Galileo spacecraft are considered. Telemetry and command capabilities are fundamental features of spacecraft design that have been successfully used for autonomous control. Also discussed is the Autonomous Redundancy and Maintenance Management Subsystem (ARMMS) concept. The software approach to autonomous control provides for modifications to the control process or the addition of new operating features during flight operations.

Turner, P. R.↗

NASA Lunabotics Robotic Mining Competition 10th Anniversary (2010-2019): Taxonomy and Technology Review

Space Mining for resources such as water ice, and regolith, which contain many elements in the form of metals, minerals, volatiles and other compounds, is a necessary step for In-Situ Space Resource Utilization (ISRU). One of the primary goals is to extract propellants from the regolith and water ice, such as oxygen and hydrogen which could then be used for in-space transportation. In addition, the space mining system can be used for various construction tasks that can benefit human and robotic exploration as well as scientific investigations based on excavated exposed topography, such as the side walls of trenches. The National Aeronautics & Space Administration (NASA) "Lunabotics" Robotic Mining Competition (RMC) is a university-level competition designed to engage and retain students in science, technology, engineering and mathematics (STEM). NASA has directly benefited from the competition by encouraging the development of innovative lunar excavation concepts from universities which has resulted in clever ideas and solutions which could be applied to an actual lunar excavation device or payload. The challenge is for students to design and build a remote controlled or autonomous excavator, called a "lunabot", which can collect and deposit a minimum of 10 kilograms of lunar simulant within 15 minutes. In recent years the goal has been changed to excavate a minimum of 1 kg of simulated icy regolith which is found under an overburden of regolith simulant. The complexities of the challenge include the abrasive characteristics of the lunar regolith simulant, the weight and size limitations of the lunabot, and the ability to control the lunabot from a remote-control center or operate it autonomously. This paper will present the results of the ten Lunabotics Robotic Mining Competitions held between May 2010 and May 2019. Each year over 50 university teams have attended, resulting in over 500 lunabot designs and subsequent prototypes. Over 6,000 university students have been part of the on-site competition at KSC. Even more students and the public were engaged via internet broadcasting and social networking media. The various designs have been cataloged and categorized here to provide information to future Lunabotics RMC mining robot designers and competitors. Categories will focus on both the mechanical design as well as the autonomy architecture/design. It is also expected to be of value for actual future space missions, as knowledge is gained from testing many innovative prototypes in simulated lunar regolith. A taxonomy of robotic excavator designs has been presented. In addition, the paper will discuss changes in learning paradigms occurring in the current generation of students, and how this competition leverages those changes to challenge students to develop skills in graduate level concepts and apply them. Examples of how this translates to hiring opportunities for commercial sponsors has also been discussed.

Robert P Mueller↗

Lunabotics Robotic Mining Competition for Universities

Space Mining for resources such as water ice, and regolith, which contain many elements in the form of metals, minerals, volatiles and other compounds, is a necessary step for In-Situ Space Resource Utilization (ISRU). One of the primary goals is to extract propellants from the regolith and water ice, such as oxygen and hydrogen which could then be used for in-space transportation. In addition, the space mining system can be used for various construction tasks that can benefit human and robotic exploration as well as scientific investigations based on excavated exposed topography, such as the side walls of trenches. The National Aeronautics & Space Administration (NASA) “Lunabotics” Robotic Mining Competition (RMC) is a university-level competition designed to engage and retain students in science, technology, engineering and mathematics (STEM). NASA has directly benefited from the competition by encouraging the development of innovative lunar excavation concepts from universities which has resulted in clever ideas and solutions which could be applied to an actual lunar excavation device or payload. The challenge is for students to design and build a remote controlled or autonomous 80 kg mass lightweight excavator, called a “lunabot”, which can collect and deposit a minimum of 10 kilograms of lunar simulant within 15 minutes. In recent years the goal has been changed to excavate a minimum of 1 kg of simulated icy regolith which is found under an overburden of regolith simulant. The complexities of the challenge include the abrasive characteristics of the lunar regolith simulant, the weight and size limitations of the lunabot, and the ability to control the lunabot from a remote mission control center or operate it autonomously. This presentation will summarize the results of the Lunabotics Robotic Mining Competitions held in May 2022. Each year, since 2010, over 50 university teams have attended, resulting in over 500 lunabot designs and subsequent prototypes. Over 6,000 university students have been part of the on-site competition at KSC, and many are employed in the space sector today with thriving careers. Even more students and the public were engaged via internet broadcasting and social networking media. Examples of how this translates to hiring opportunities for commercial sponsors will also be discussed. Overall, this competition has proven to be popular with multi-disciplinary university senior design classes and a valuable tool for NASA and academia in educating and inspiring the next generation of space engineers.

Lunabotics↗

Responsible Adoption of Artificial Intelligence (AI) in Electric Grid Operations

The future of the grid will be powered by AI—or undermined by it. Artificial intelligence is rapidly reshaping grid operations, improving fault detection, forecasting accuracy, and real-time optimization. As AI systems move closer to operational decision loops, however, they introduce new consequence pathways: expanded attack surfaces, model integrity risks, regulatory exposure, and human-automation challenges. This talk presents a consequence-driven framework for deploying AI responsibly in the electric grid. Attendees will gain practical strategies to strengthen resilience, boost reliability, and deploy AI securely — ensuring the grid of the future is not only smarter but safer.

25 - ENERGY STORAGE↗

The Jet Propulsion Laboratory shared control architecture and implementation

A hardware and software environment for shared control of telerobot task execution has been implemented. Modes of task execution range from fully teleoperated to fully autonomous as well as shared where hand controller inputs from the human operator are mixed with autonomous system inputs in real time. The objective of the shared control environment is to aid the telerobot operator during task execution by merging real-time operator control from hand controllers with autonomous control to simplify task execution for the operator. The operator is the principal command source and can assign as much autonomy for a task as desired. The shared control hardware environment consists of two PUMA 560 robots, two 6-axis force reflecting hand controllers, Universal Motor Controllers for each of the robots and hand controllers, a SUN4 computer, and VME chassis containing 68020 processors and input/output boards. The operator interface for shared control, the User Macro Interface (UMI), is a menu driven interface to design a task and assign the levels of teleoperated and autonomous control. The operator also sets up the system monitor which checks safety limits during task execution. Cartesian-space degrees of freedom for teleoperated and/or autonomous control inputs are selected within UMI as well as the weightings for the teleoperation and autonmous inputs. These are then used during task execution to determine the mix of teleoperation and autonomous inputs. Some of the autonomous control primitives available to the user are Joint-Guarded-Move, Cartesian-Guarded-Move, Move-To-Touch, Pin-Insertion/Removal, Door/Crank-Turn, Bolt-Turn, and Slide. The operator can execute a task using pure teleoperation or mix control execution from the autonomous primitives with teleoperated inputs. Presently the shared control environment supports single arm task execution. Work is presently underway to provide the shared control environment for dual arm control. Teleoperation during shared control is only Cartesian space control and no force-reflection is provided. Force-reflecting teleoperation and joint space operator inputs are planned extensions to the environment.

Backes, Paul G.↗

Design of an Excavation Robot: Regolith Advanced Surface Systems Operations Robot (RASSOR) 2.0

To continue on a sustainable and flexible path, NASA needs to address the challenge of collecting and moving large amounts of regolith at the destination. Acquiring the water resources on Mars will require mining significant quantities of regolith and this is not possible with the state-of-the-art low mass excavation systems. Low gravity environments (Mars = 3/8 G) and launch mass restrictions limit the traction and the resulting reaction force of the vehicle, making current terrestrial techniques impractical. This project addressed this challenge by developing a completely new technology that can mine large quantities of regolith on Mars. Recent measurements by the “Curiosity” rover on Mars have found that the regolith contains ~ 2% water by weight globally, ~4% in Jezero Crater (Human Architecture Team’s reference landing site), and much more at the poles(Leshin et al, 2013). RASSOR 2.0 is a planetary excavator, which has a mass of 66 kg, with a 0.38 kg vehicle mass per kilogram, per hour of excavation rate and power usage of 4 W per kg of regolith excavation rate. A single RASSOR 2.0 can excavate a minimum of 2.7 metric tons of regolith per day.This is accomplished by using counteracting excavation forces on two opposing digging implements called bucket drums and an autonomous mining control system. This work has addressed several major research areas outlined in the NASA Technology Area (TA) 04 Robotics & Autonomous Systems and TA 07 Human Destination Systems roadmaps. This project started at Technology Readiness Level (TRL) 4 as a low fidelity “proof of concept” prototype which has successfully demonstrated basic regolith simulant excavation functionality in a lab-scale gravity off load test. The foundational technology described here was awarded US patent number: US 9027265 for a “Zero horizontal reaction force excavator” on May 12, 2015.

RASSOR↗

Automated orbital rendezvous considerations

The control of the rendezvous vehicle during proximity operations is considered. It is shown how fuzzy sets can be used for autonomous vehicle control to model the human capability of common sense reasoning. Such models are integrated with expert systems and engineering control systems technology to create a system that performs comparably to a manned system.

Lea, Robert N.↗

Integrated airframe/propulsion control system architectures (IAPSA) study

Three integrated airframe/propulsion control system (ACS) architectures have been developed and are discussed. The baseline is a state of the art design which integrates autonomous propusion control and airframe flight control systems. Two alternate ACSs for the 1990s using emerging technologies were developed and are compared with each other and the baseline. One of these, designated D/D, uses parallel distributed processing, while the other, designated C/D, centralizes the processing into two centrally located redundant electronics complex. The C/D system locates all redundant computing elements and interfacing electronics in two boxes with optical sensor and actuation devices optically connected to the two boxes. Evaluation reveals the C/D architecture to be better than the other two in five of ten categories; D/D is superior in only two of the ten.

Stern,, A. d.↗

A Virtual Mission Operations Center: Collaborative Environment

The Virtual Mission Operations Center - Collaborative Environment (VMOC-CE) intent is to have a central access point for all the resources used in a collaborative mission operations environment to assist mission operators in communicating on-site and off-site in the investigation and resolution of anomalies. It is a framework that as a minimum incorporates online chat, realtime file sharing and remote application sharing components in one central location. The use of a collaborative environment in mission operations opens up the possibilities for a central framework for other project members to access and interact with mission operations staff remotely. The goal of the Virtual Mission Operations Center (VMOC) Project is to identify, develop, and infuse technology to enable mission control by on-call personnel in geographically dispersed locations. In order to achieve this goal, the following capabilities are needed: Autonomous mission control systems Automated systems to contact on-call personnel Synthesis and presentation of mission control status and history information Desktop tools for data and situation analysis Secure mechanism for remote collaboration commanding Collaborative environment for remote cooperative work The VMOC-CE is a collaborative environment that facilitates remote cooperative work. It is an application instance of the Virtual System Design Environment (VSDE), developed by NASA Goddard Space Flight Center's (GSFC) Systems Engineering Services & Advanced Concepts (SESAC) Branch. The VSDE is a web-based portal that includes a knowledge repository and collaborative environment to serve science and engineering teams in product development. It is a "one stop shop" for product design, providing users real-time access to product development data, engineering and management tools, and relevant design specifications and resources through the Internet. The initial focus of the VSDE has been to serve teams working in the early portion of the system/product lifecycle - concept development, proposal preparation, and formulation. The VMOC-CE expands the application of the VSDE into the operations portion of the system lifecycle. It will enable meaningful and real-time collaboration regardless of the geographical distribution of project team members. Team members will be able to interact in satellite operations, specifically for resolving anomalies, through access to a desktop computer and the Internet. Mission Operations Management will be able to participate and monitor up to the minute status of anomalies or other mission operations issues. In this paper we present the VMOC-CE project, system capabilities, and technologies.

Medina, Barbara↗

Analytic investigation of the AEM-A/HCMM attitude control system performance

The Heat Capacity Mapping Mission (HCMM), scheduled for launch in 1978, will be three-axis stabilized relative to the earth in a 600-kilometer altitude, polar orbit. The autonomous attitude control system consists of three torquing coils and a momentum wheel driven in response to error signals computed from data received from an infrared horizon sensor and a magnetometer. This paper presents a simple model of the attitude dynamics and derives the equations that determine the stability of the system during both attitude acquisition (acquisition-mode) and mission operations (mission-mode). Modifications to the proposed mission-mode control laws which speed the system's response to transient attitude errors and reduce the steady-state attitude errors are suggested. Numerical simulations are performed to validate the results obtained with the simple model.

Lerner, G. M.↗