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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 217 records · Page 12

Orbital Express Mission Operations Planning and Resource Management using ASPEN

As satellite equipment and mission operations become more costly, the drive to keep working equipment running with less man-power rises.Demonstrating the feasibility of autonomous satellite servicing was the main goal behind the Orbital Express (OE) mission. Planning the satellite mission operations for OE required the ability to create a plan which could be executed autonomously over variable conditions. The Automated-Scheduling and Planning Environment (ASPEN)tool, developed at the Jet Propulsion Laboratory, was used to create the schedule of events in each daily plan for the two satellites of the OE mission. This paper presents an introduction to the ASPEN tool, the constraints of the OE domain, the variable conditions that were presented within the mission, and the solution to operations that ASPEN provided. ASPEN has been used in several other domains, including research rovers, Deep Space Network scheduling research, and in flight operations for the ASE project's EO1 satellite. Related work is discussed, as are the future of ASPEN and the future of autonomous satellite servicing.

Automated Scheduling and Planning Environment (ASP↗

Autonomous rendezvous and docking: A commercial approach to on-orbit technology validation

SpARC, in conjunction with its corporate affiliates, is planning an on-orbit validation of autonomous rendezvous and docking (ARD) technology. The emphasis in this program is to utilize existing technology and commercially available components wherever possible. The primary subsystems to be validated by this demonstration include GPS receivers for navigation, a video-based sensor for proximity operations, a fluid connector mechanism to demonstrate fluid resupply capability, and a compliant, single-point docking mechanism. The focus for this initial experiment will be ELV based and will make use of two residual Commercial Experiment Transporter (COMET) service modules. The first COMET spacecraft will be launched in late 1992 and will serve as the target vehicle. After the second COMET spacecraft has been launched in late 1994, the ARD demonstration will take place. The service module from the second COMET will serve as the chase vehicle.

Tchoryk, Peter, Jr.↗

Software assurance of autonomous spacecraft control

The work described addresses assurance of a planning and execution software system being added to an in-orbit CubeSat to demonstrate autonomous control of that spacecraft. Our focus was on how to develop assurance of the correct operation of the added software in its operational context, our approach to which was to use an assurance case to guide and organize the information involved.

Bocchino, Robert↗

Software for Automation of Real-Time Agents, Version 2

Version 2 of Closed Loop Execution and Recovery (CLEaR) has been developed. CLEaR is an artificial intelligence computer program for use in planning and execution of actions of autonomous agents, including, for example, Deep Space Network (DSN) antenna ground stations, robotic exploratory ground vehicles (rovers), robotic aircraft (UAVs), and robotic spacecraft. CLEaR automates the generation and execution of command sequences, monitoring the sequence execution, and modifying the command sequence in response to execution deviations and failures as well as new goals for the agent to achieve. The development of CLEaR has focused on the unification of planning and execution to increase the ability of the autonomous agent to perform under tight resource and time constraints coupled with uncertainty in how much of resources and time will be required to perform a task. This unification is realized by extending the traditional three-tier robotic control architecture by increasing the interaction between the software components that perform deliberation and reactive functions. The increase in interaction reduces the need to replan, enables earlier detection of the need to replan, and enables replanning to occur before an agent enters a state of failure.

Fisher, Forest↗

Research and applications: Artificial intelligence

Research in the field of artificial intelligence is discussed. The focus of recent work has been the design, implementation, and integration of a completely new system for the control of a robot that plans, learns, and carries out tasks autonomously in a real laboratory environment. The computer implementation of low-level and intermediate-level actions; routines for automated vision; and the planning, generalization, and execution mechanisms are reported. A scenario that demonstrates the approximate capabilities of the current version of the entire robot system is presented.

Raphael, B.↗

Autonomously generating operations sequences for a Mars Rover using AI-based planning

This paper discusses a proof-of-concept prototype for ground-based automatic generation of validated rover command sequences from highlevel science and engineering activities. This prototype is based on ASPEN, the Automated Scheduling and Planning Environment. This Artificial Intelligence (AI) based planning and scheduling system will automatically generate a command sequence that will execute within resource constraints and satisfy flight rules.

Mars Rover↗

A High-Performance Computing GNSS-aware Path Planning Algorithm for Safe Urban Flight Operations

The emergence and development of advanced technologies and vehicle types have created a growing demand for new forms of flight operations. These new and increasingly complex operational paradigms, such as Advanced and Urban Air Mobility (AAM/UAM), present regulatory authorities and the aviation community with several design-and-implementation challenges – particularly for highly autonomous vehicles. An overarching and daunting task is to develop protocols that can integrate these operations without compromising safety or disrupting traditional airspace operations. A shift toward a more predictive, autonomous, risk mitigation capability becomes critical to meet this challenge. This paper proposes and evaluates a computationally-efficient path planning approach to perform pre-flight planning and autonomous in-flight re-routing to minimize exposures to selected hazards. In our evaluation, hazards associated with degraded and missing critical GPS navigation data are considered. In this paper, we first present a high-performance computing path planning approach based on an adapted Bellman-Ford algorithm, developed in the CUDA programming language. Using the adapted path planning algorithm, we test this algorithm when encountering issues with GPS quality, and deliver an implementation that can produce flight paths that minimize exposure to risks, while maintaining a low computational burden. In our evaluation, the computation of periodic and aperiodic path updates are evaluated, prioritizing specific events as triggers for updates, based on changes to satellite availability. These critical events can lead to significant exposure to navigational hazards if not dealt with correctly.

GNSS↗

A High-Performance Computing GNSS-aware Path Planning Algorithm for Safe Urban Flight Operations

The emergence and development of advanced technologies and vehicle types have created a growing demand for new forms of flight operations. These new and increasingly complex operational paradigms, such as Advanced and Urban Air Mobility (AAM/UAM), present regulatory authorities and the aviation community with several design-and-implementation challenges – particularly for highly autonomous vehicles. An overarching and daunting task is to develop protocols that can integrate these operations without compromising safety or disrupting traditional airspace operations. A shift toward a more predictive, autonomous, risk mitigation capability becomes critical to meet this challenge. This paper proposes and evaluates a computationally-efficient path planning approach to perform pre-flight planning and autonomous in-flight re-routing to minimize exposures to selected hazards. In our evaluation, hazards associated with degraded and missing critical GPS navigation data are considered. In this paper, we first present a high-performance computing path planning approach based on an adapted Bellman-Ford algorithm, developed in the CUDA programming language. Using the adapted path planning algorithm, we test this algorithm when encountering issues with GPS quality, and deliver an implementation that can produce flight paths that minimize exposure to risks, while maintaining a low computational burden. In our evaluation, the computation of periodic and aperiodic path updates are evaluated, prioritizing specific events as triggers for updates, based on changes to satellite availability. These critical events can lead to significant exposure to navigational hazards if not dealt with correctly.

GNSS↗

Pathfinding for Airspace with Autonomous Vehicles (PAAV) ACAS Xr Terminal Area Simulation Overview

This presentation provides an overview of an upcoming human-in-the-loop simulation planned by the Pathfinding for Airspace with Autonomous Vehicles (PAAV) subproject, as part of the Air Traffic Management eXploration project. The study will investigate Detect and Avoid (DAA) concepts in and around the DAA terminal area (DTA). The DTA has received little investigation in real-time, pilot-in-the-loop simulation. This study proposes to use current remotely piloted aircraft system (RPAS) pilots to investigate the effectiveness of current DTA requirements using the FAA's Airborne Collision Avoidance System X for Rotorcraft (ACAS Xr) as the DAA system under test. The findings of this stufy will be used to inform DTA and ACAS Xr standards development. This presentation will be provided to RTCA Special Committee 228 as an overview and as an opportunity to collect feedback from the larger RPAS/DAA community on the study design and key scenarios and metrics. The presentation provides a brief overview of open areas of research with ACAS Xr, the experimental design, the simulation environment and the simulation schedule.

advanced air mobility↗

Situational reaction and planning

One problem faced in designing an autonomous mobile robot system is that there are many parameters of the system to define and optimize. While these parameters can be obtained for any given situation determining what the parameters should be in all situations is difficult. The usual solution is to give the system general parameters that work in all situations, but this does not help the robot to perform its best in a dynamic environment. Our approach is to develop a higher level situation analysis module that adjusts the parameters by analyzing the goals and history of sensor readings. By allowing the robot to change the system parameters based on its judgement of the situation, the robot will be able to better adapt to a wider set of possible situations. We use fuzzy logic in our implementation to reduce the number of basic situations the controller has to recognize. For example, a situation may be 60 percent open and 40 percent corridor, causing the optimal parameters to be somewhere between the optimal settings for the two extreme situations.

Yen, John↗

Exploiting map plans as resources for action

When plans are used as programs for controlling the action of autonomous or teleoperated robots, their abstract representation can easily obscure a great deal of the critical knowledge that originally led to the planned course of action. An autonomous vehicle experiment is highlighted which illustrates how the information barriers created by abstraction can result in undesirable action. It is then shown how the same task can be performed correctly using plans as a resource for action. As a result of this simple change in outlook, problems requiring opportunistic reaction to unexpected changes in the environment can be solved.

Payton, David↗

Lyapunov-Based Sensor Failure Detection And Recovery For The Reverse Water Gas Shift Process

Livingstone, a model-based AI software system, is planned for use in the autonomous fault diagnosis, reconfiguration, and control of the oxygen-producing reverse water gas shift (RWGS) process test-bed located in the Applied Chemistry Laboratory at KSC. In this report the RWGS process is first briefly described and an overview of Livingstone is given. Next, a Lyapunov-based approach for detecting and recovering from sensor failures, differing significantly from that used by Livingstone, is presented. In this new method, models used are in terms of the defining differential equations of system components, thus differing from the qualitative, static models used by Livingstone. An easily computed scalar inequality constraint, expressed in terms of sensed system variables, is used to determine the existence of sensor failures. In the event of sensor failure, an observer/estimator is used for determining which sensors have failed. The theory underlying the new approach is developed. Finally, a recommendation is made to use the Lyapunov-based approach to complement the capability of Livingstone and to use this combination in the RWGS process.

Haralambous, Michael G.↗

LYAPUNOV-Based Sensor Failure Detection and Recovery for the Reverse Water Gas Shift Process

Livingstone, a model-based AI software system, is planned for use in the autonomous fault diagnosis, reconfiguration, and control of the oxygen-producing reverse water gas shift (RWGS) process test-bed located in the Applied Chemistry Laboratory at KSC. In this report the RWGS process is first briefly described and an overview of Livingstone is given. Next, a Lyapunov-based approach for detecting and recovering from sensor failures, differing significantly from that used by Livingstone, is presented. In this new method, models used are in t e m of the defining differential equations of system components, thus differing from the qualitative, static models used by Livingstone. An easily computed scalar inequality constraint, expressed in terms of sensed system variables, is used to determine the existence of sensor failures. In the event of sensor failure, an observer/estimator is used for determining which sensors have failed. The theory underlying the new approach is developed. Finally, a recommendation is made to use the Lyapunov-based approach to complement the capability of Livingstone and to use this combination in the RWGS process.

Haralambous, Michael G.↗

Tactical Maneuvering Using Immunized Sequence Selection

This paper describes a tactical maneuvering system that uses an artificial immune system based approach for selecting maneuver sequences. This approach combines the problem solving abilities of genetic algorithms with the memory retention characteristics of an immune system. Of significant importance here is the fact that the tactical maneuvering system can make time-critical decisions to accomplish near-term objectives within a dynamic environment. These objectives can be received from a human operator, autonomous executive, or various flight planning specialists. Simulation tests were performed using a high performance military aircraft model. Results demonstrate the potential of using immunized sequence selection in order to accomplish tactical maneuvering objectives ranging from flying to a location while avoiding unforeseen obstacles, to performing relative positioning in support of air combat maneuvering.

Kaneshige, John↗

Performance Efficient Launch Vehicle Recovery and Reuse

For decades, economic reuse of launch vehicles has been an elusive goal. Recent attempts at demonstrating elements of launch vehicle recovery for reuse have invigorated a debate over the merits of different approaches. The parameter most often used to assess the cost of access to space is dollars-per-kilogram to orbit. When comparing reusable vs. expendable launch vehicles, that ratio has been shown to be most sensitive to the performance lost as a result of enabling the reusability. This paper will briefly review the historical background and results of recent attempts to recover launch vehicle assets for reuse. The business case for reuse will be reviewed, with emphasis on the performance expended to recover those assets, and the practicality of the most ambitious reuse concept, namely propulsive return to the launch site. In 2015, United Launch Alliance (ULA) announced its Sensible, Modular, Autonomous Return Technology (SMART) reuse plan for recovery of the booster module for its new Vulcan launch vehicle. That plan employs a non-propulsive approach where atmospheric entry, descent and landing (EDL) technologies are utilized. Elements of such a system have a wide variety of applications, from recovery of launch vehicle elements in suborbital trajectories all the way to human space exploration. This paper will include an update on ULA's booster module recovery approach, which relies on Hypersonic Inflatable Aerodynamic Decelerator (HIAD) and Mid-Air Retrieval (MAR) technologies, including its concept of operations (ConOps). The HIAD design, as well as parafoil staging and MAR concepts, will be discussed. Recent HIAD development activities and near term plans including scalability, next generation materials for the inflatable structure and heat shield, and gas generator inflation systems will be provided. MAR topics will include the ConOps for recovery, helicopter selection and staging, and the state of the art of parachute recovery systems using large parafoils for space asset recovery and high altitude deployment. The next proposed HIAD flight demonstration is called HULA (for HIAD on ULA), and will feature a 6m diameter HIAD. An update for the HULA concept will be provided in this paper. As proposed, this demonstration will fly as a secondary payload on an Atlas mission. The Centaur upper stage provides the reentry pointing, deorbit burn, and entry vehicle spin up. The flight test will culminate with a recovery of the HIAD using MAR. HULA will provide data from a Low Earth Orbit (LEO) return aeroheating environment that enables predictive model correlation and refinement. The resultant reduction in performance uncertainties should lead to design efficiencies that are increasingly significant at larger scales. Relevance to human scale Mars EDL using a HIAD will also be presented, and the applicability of the data generated from both HULA and SMART Vulcan flights, and its value for NASA's human exploration efforts will be discussed. A summary and conclusion will follow.

Reed, John G.↗

Future Free Flyer Science on the ISS

The Astrobee Research Facility will maintain three identical free-flying Astrobee robots on the ISS. After the Astrobees are launched and commissioned in 2018, they will replace the SPHERES robots that have been operating on the ISS since 2006. Astrobee can fly autonomously throughout most of the US section of the ISS interior, but cannot operate outside the ISS. Astrobee is propelled by a pair of battery-operated fans, and can autonomously return to a docking station to recharge, so it can perform most activities without requiring any astronaut support. It carries a suite of six cameras, a two degree-of-freedom (DOF) arm with a gripper that can grasp ISS handrails and other objects, and three payload bays that provide power and data for guest science hardware. It can autonomously execute hours-long plans (for example, sensor surveys) or be teleoperated live from the ground or by astronauts.

Katterhagen, Aric J.↗

Robotic Manipulation Testbeds with HPSC

Interoperability and scalability of robotic manipulators will be key to develop and sustain a lunar surface and cislunar ecosystem. From in-space servicing, assembly, and manufacturing (ISAM) to logistics, maintenance, and science operations, robotic manipulation is a critical NASA capability need and the demand for high-performance spaceflight computing will only rise as robotic tasks become more autonomous. With increased complexity, testbeds for research, feasibility studies, and technology demonstrations will be essential. The Dexterous Robotics Team at NASA Johnson Space Center has established multiple robotic manipulation testbeds taking a supervised autonomous remote operations approach and plans to infuse High-Performance Spaceflight Computing (HPSC) to emulate the flight environment and close the gap between space technology development and flight operations.

Alex Sowell↗

NAS Exploratory Concepts & Technologies (NExCT) Upper Class E Traffic Management (ETM) Collaborative Evaluation #1 (CE-1)

NASA, in partnership with AeroVironment and Aerostar, recently demonstrated a first-of-its-kind air traffic management concept that could pave the way for aircraft to safely operate at higher altitudes. This work seeks to open the door for increased internet coverage, improved disaster response, expanded scientific missions, and even supersonic flight. The concept is referred to as an Upper-Class E traffic management, or ETM. NASA and its partners have developed an ETM traffic management system that allows aircraft to autonomously share location and flight plans, enabling aircraft to stay safely separated. This concept was demonstrated during the recent traffic management simulation in the Airspace Operations Laboratory at Ames, data from multiple air vehicles was displayed across dozens of traffic control monitors and shared with partner computers off site. The study details and the initial results are presented at a regular, informal ETM industry meetings held virtually.

Upper Class E Traffic Management (ETM)↗