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At least 217 records · Page 12

Automated Operations Development for Advanced Exploration Systems

Automated space operations command and control software development and its implementation must be an integral part of the vehicle design effort. The software design must encompass autonomous fault detection, isolation, recovery capabilities and also provide "single button" intelligent functions for the crew. Development, operations and safety approval experience with the Timeliner system onboard the International Space Station (ISS), which provided autonomous monitoring with response and single command functionality of payload systems, can be built upon for future automated operations as the ISS Payload effort was the first and only autonomous command and control system to be in continuous execution (6 years), 24 hours a day, 7 days a week within a crewed spacecraft environment. Utilizing proven capabilities from the ISS Higher Active Logic (HAL) System, along with the execution component design from within the HAL 9000 Space Operating System, this design paper will detail the initial HAL System software architecture and interfaces as applied to NASA's Habitat Demonstration Unit (HDU) in support of the Advanced Exploration Systems, Autonomous Mission Operations project. The development and implementation of integrated simulators within this development effort will also be detailed and is the first step in verifying the HAL 9000 Integrated Test-Bed Component [2] designs effectiveness. This design paper will conclude with a summary of the current development status and future development goals as it pertains to automated command and control for the HDU.

Haddock, Angie T.↗

Automated Operations Development for Advanced Exploration Systems

Automated space operations command and control software development and its implementation must be an integral part of the vehicle design effort. The software design must encompass autonomous fault detection, isolation, recovery capabilities and also provide single button intelligent functions for the crew. Development, operations and safety approval experience with the Timeliner system on-board the International Space Station (ISS), which provided autonomous monitoring with response and single command functionality of payload systems, can be built upon for future automated operations as the ISS Payload effort was the first and only autonomous command and control system to be in continuous execution (6 years), 24 hours a day, 7 days a week within a crewed spacecraft environment. Utilizing proven capabilities from the ISS Higher Active Logic (HAL) System [1] , along with the execution component design from within the HAL 9000 Space Operating System [2] , this design paper will detail the initial HAL System software architecture and interfaces as applied to NASA s Habitat Demonstration Unit (HDU) in support of the Advanced Exploration Systems, Autonomous Mission Operations project. The development and implementation of integrated simulators within this development effort will also be detailed and is the first step in verifying the HAL 9000 Integrated Test-Bed Component [2] designs effectiveness. This design paper will conclude with a summary of the current development status and future development goals as it pertains to automated command and control for the HDU.

Haddock, Angie↗

Robust Path Planning and Feedback Design Under Stochastic Uncertainty

Autonomous vehicles require optimal path planning algorithms to achieve mission goals while avoiding obstacles and being robust to uncertainties. The uncertainties arise from exogenous disturbances, modeling errors, and sensor noise, which can be characterized via stochastic models. Previous work defined a notion of robustness in a stochastic setting by using the concept of chance constraints. This requires that mission constraint violation can occur with a probability less than a prescribed value.In this paper we describe a novel method for optimal chance constrained path planning with feedback design. The approach optimizes both the reference trajectory to be followed and the feedback controller used to reject uncertainty. Our method extends recent results in constrained control synthesis based on convex optimization to solve control problems with nonconvex constraints. This extension is essential for path planning problems, which inherently have nonconvex obstacle avoidance constraints. Unlike previous approaches to chance constrained path planning, the new approach optimizes the feedback gain as wellas the reference trajectory.The key idea is to couple a fast, nonconvex solver that does not take into account uncertainty, with existing robust approaches that apply only to convex feasible regions. By alternating between robust and nonrobust solutions, the new algorithm guarantees convergence to a global optimum. We apply the new method to an unmanned aircraft and show simulation results that demonstrate the efficacy of the approach.

autonomuys vehicles↗

Redesigning large-scale multimodal transit networks with shared autonomous mobility services

Here, this study addresses a large-scale multimodal transit network design problem, with Shared Autonomous Mobility Services (SAMS) as both transit feeders and an origin-to-destination mode. The framework captures spatial demand and modal characteristics, considers intermodal transfers and express services, determines transit infrastructure investment and path flows, and generates transit routes. A system-optimal multimodal transit network is designed with minimum total door-to-door generalized costs of users and operators, satisfying transit origin-destination demand within a pre-set infrastructure budget. Firstly, the geography, demand, and modes in each zone are characterized with continuous approximation. The decisions of network link investment and multimodal path flows in zonal connection optimization are formulated as a minimum-cost multi-commodity network flow (MCNF) problem and solved efficiently with a mixed-integer linear programming (MILP) solver. Subsequently, the route generation problem is solved by expanding the MCNF formulation to minimize intramodal transfers. The model is illustrated through a set of experiments with the Chicago network comprised of 50 zones and seven modes, under three scenarios. The computational results present savings in traveler journey time and operator cost demonstrating the potential benefits of collaboration between multimodal transit systems and SAMS.

Autonomous vehicles↗

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.↗

System Engineering Paper

The Iowa State University team, Team LunaCY, is composed of the following sub-teams: the main student organization, the Lunabotics Club; a senior mechanical engineering design course, ME 415; a senior multidisciplinary design course, ENGR 466; and a senior design course from Wartburg College in Waverly, Iowa. Team LunaCY designed and fabricated ART-E III, Astra Robotic Tractor- Excavator the Third, for the team's third appearance in the NASA Lunabotic Mining competition. While designing ART-E III, the team had four main goals for this year's competition:to reduce the total weight of the robot, to increase the amount of regolith simulant mined, to reduce dust, and to make ART-E III autonomous. After many designs and research, a final robot design was chosen that obtained all four goals of Team LunaCY. A few changes Team LunaCY made this year was to go to the electrical, computer, and software engineering club fest at Iowa State University to recruit engineering students to accomplish the task of making ART-E III autonomous. Team LunaCY chose to use LabView to program the robot and various sensors were installed to measure the distance between the robot and the surroundings to allow ART-E III to maneuver autonomously. Team LunaCY also built a testing arena to test prototypes and ART-E III in. To best replicate the competition arena at the Kennedy Space Center, a regolith simulant was made from sand, QuickCrete, and fly ash to cover the floor of the arena. Team LunaCY also installed fans to allow ventilation in the arena and used proper safety attire when working in the arena . With the additional practice in the testing arena and innovative robot design, Team LunaCY expects to make a strong appearance at the 2012 NASA Lunabotic Mining Competition. .

Heise, James↗

Autonomous Rover Traverse and Precise Arm Placement on Remotely Designated Targets

Exploring planetary surfaces typically involves traversing challenging and unknown terrain and acquiring in-situ measurements at designated locations using arm-mounted instruments. We present field results for a new implementation of an autonomous capability that enables a rover to traverse and precisely place an arm-mounted instrument on remote targets. Using point-and-click mouse commands, a scientist designates targets in the initial imagery acquired from the rover's mast cameras. The rover then autonomously traverse the rocky terrain for a distance of 10 - 15 m, tracks the target(s) of interest during the traverse, positions itself for approaching the target, and then precisely places an arm-mounted instrument within 2-3 cm from the originally designated target. The rover proceeds to acquire science measurements with the instrument. This work advances what has been previously developed and integrated on the Mars Exploration Rovers by using algorithms that are capable of traversing more rock-dense terrains, enabling tight thread-the-needle maneuvers. We integrated these algorithms on the newly refurbished Athena Mars research rover and fielded them in the JPL Mars Yard. We conducted 43 runs with targets at distances ranging from 5 m to 15 m and achieved a success rate of 93% for placement of the instrument within 2-3 cm.

Mars Exploration Rover (MER)↗

Autonomous rover traverse and precise arm placement on remotely designated targets

Exploring planetary surfaces typically involves traversing challenging and unknown terrain and acquiring insitu measurements at designated locations using arm-mounted instruments. We present field results for a new implementation of an autonomous capability that enables a rover to traverse and precisely place an arm-mounted instrument on remote targets. Using point-and-click mouse commands, a scientist designates targets in the initial imagery acquired from the rover’s mast cameras. The rover then autonomously traverses the rocky terrain for a distance of 10 – 15 m, tracks the target(s) of interest during the traverse, positions itself for approaching the target, and then precisely places an arm-mounted instrument within 2-3 cm from the originally designated target. The rover proceeds to acquire science measurements with the instrument. This work advances what has been previously developed and integrated on the Mars Exploration Rovers by using algorithms that are capable of traversing more rock-dense terrains, enabling tight thread-the-needle maneuvers. We integrated these algorithms on the newly refurbished Athena Mars research rover and fielded them in the JPL Mars Yard. We conducted 43 runs with targets at distances ranging from 5 m to 15 m and achieved a success rate of 93% for placement of the instrument within 2-3 cm.

Volpe, Richard↗

Intermediate Levels of Autonomy within the SSM/PMAD Breadboard

The Space Station Module Power Management and Distribution (SSM/PMAD) bread-board is a test bed for the development of advanced power system control and automation. Software control in the SSM/PMAD breadboard is through co-operating systems, called Autonomous Agents. Agents can be a mixture of algorithmic software and expert systems. The early SSM/PMAD system was envisioned as being completely autonomous. It soon became apparent, though, that there would always be a need for human intervention, at least as long as a human interacts with the system in any way. In a system designed only for autonomous operation, manual intervention meant taking full control of the whole system, and loosing whatever expertise was in the system. Several methods for allowing humans to interact at an appropriate level of control were developed. This paper examines some of these intermediate modes of autonomy. The least humanly intrusive mode is simple monitoring. The ability to modify future behavior by altering a schedule involves high-level interaction. Modification of operating activities comes next. The coarsest mode of control is individual, unplanned operation of individual Power System components. Each of these levels is integrated into the SSM/PMAD breadboard, with support for the user (such as warnings of the consequences of control decisions) at every level.

Dugal-Whitehead, Norma R.↗

Exploring with PAM: Prospecting ANTS Missions for Solar System Surveys

ANTS (Autonomous Nano-Technology Swarm), a large (1000 member) swarm of nano to picoclass (10 to 1 kg) totally autonomous spacecraft, are being developed as a NASA advanced mission concept. ANTS, based on a hierarchical insect social order, use an evolvable, self-similar, hierarchical neural system in which individual spacecraft represent the highest level nodes. ANTS uses swarm intelligence attained through collective, cooperative interactions of the nodes at all levels of the system. At the highest levels this can take the form of cooperative, collective behavior among the individual spacecraft in a very large constellation. The ANTS neural architecture is designed for totally autonomous operation of complex systems including spacecraft constellations. The ANTS (Autonomous Nano Technology Swarm) concept has a number of possible applications. A version of ANTS designed for surveying and determining the resource potential of the asteroid belt, called PAM (Prospecting ANTS Mission), is examined here.

Clark, P. E.↗

Proceedings of the 8th Annual Summer Conference: NASA/USRA Advanced Design Program

Papers presented at the 8th Annual Summer Conference are categorized as Space Projects and Aeronautics projects. Topics covered include: Systematic Propulsion Optimization Tools (SPOT), Assured Crew Return Vehicle Post Landing Configuration Design and Test, Autonomous Support for Microorganism Research in Space, Bioregenerative System Components for Microgravity, The Extended Mission Rover (EMR), Planetary Surface Exploration MESUR/Autonomous Lunar Rover, Automation of Closed Environments in Space for Human Comfort and Safety, Walking Robot Design, Extraterrestrial Surface Propulsion Systems, The Design of Four Hypersonic Reconnaissance Aircraft, Design of a Refueling Tanker Delivering Liquid Hydrogen, The Design of a Long-Range Megatransport Aircraft, and Solar Powered Multipurpose Remotely Powered Aircraft.

Source record↗

Information for Successful Interaction with Autonomous Systems

Interaction in heterogeneous mission operations teams is not well matched to classical models of coordination with autonomous systems. We describe methods of loose coordination and information management in mission operations. We describe an information agent and information management tool suite for managing information from many sources, including autonomous agents. We present an integrated model of levels of complexity of agent and human behavior, which shows types of information processing and points of potential error in agent activities. We discuss the types of information needed for diagnosing problems and planning interactions with an autonomous system. We discuss types of coordination for which designs are needed for autonomous system functions.

Malin, Jane T.↗

On-Orbit Measurements of the ISS Atmosphere by the Vehicle Cabin Atmosphere Monitor

We report on trace gas and major atmospheric constituents results obtained by the Vehicle Cabin Atmosphere Monitor (VCAM) during operations aboard the International Space Station (ISS). VCAM is an autonomous environmental monitor based on a miniature gas chromatograph/mass spectrometer. It was flown to the ISS on shuttle mission STS-131 and commenced operations on 6/10/10. VCAM provides measurements of ppb-to-ppm levels of volatile trace-gas constituents, and of the atmospheric major constituents (nitrogen, oxygen, argon, and carbon dioxide) in a space vehicle or station. It is designed to operate autonomously and maintenance-free, approximately once per day, with a self-contained gas supply sufficient for a one-year lifetime. VCAM is designed to detect and identify 90% of the target compounds at their 180-day Spacecraft Maximum Allowable Concentration levels.

cabin atmosphere↗

Human-Centered Design for the Personal Satellite Assistant

The Personal Satellite Assistant (PSA) is a softball-sized flying robot designed to operate autonomously onboard manned spacecraft in pressurized micro-gravity environments. We describe how the Brahms multi-agent modeling and simulation environment in conjunction with a KAoS agent teamwork approach can be used to support human-centered design for the PSA.

Bradshaw, Jeffrey M.↗

The Planning Execution Monitoring Architecture

The Planning Execution Monitoring (PEM) architecture is a design concept for developing autonomous cockpit command and control software. The PEM architecture is designed to reduce the operations costs in the space transportation system through the use of automation while improving safety and operability of the system. Specifically, the PEM autonomous framework enables automatic performance of many vehicle operations that would typically be performed by a human. Also, this framework supports varying levels of autonomous control, ranging from fully automatic to fully manual control. The PEM autonomous framework interfaces with the core flight software to perform flight procedures. It can either assist human operators in performing procedures or autonomously execute routine cockpit procedures based on the operational context. Most importantly, the PEM autonomous framework promotes and simplifies the capture, verification, and validation of the flight operations knowledge. Through a hierarchical decomposition of the domain knowledge, the vehicle command and control capabilities are divided into manageable functional "chunks" that can be captured and verified separately. These functional units, each of which has the responsibility to manage part of the vehicle command and control, are modular, re-usable, and extensible. Also, the functional units are self-contained and have the ability to plan and execute the necessary steps for accomplishing a task based upon the current mission state and available resources. The PEM architecture has potential for application outside the realm of spaceflight, including management of complex industrial processes, nuclear control, and control of complex vehicles such as submarines or unmanned air vehicles.

Wang, Lui↗

Damage Detection and Verification System (DDVS) for In-Situ Health Monitoring

Project presentation for Game Changing Program Smart Book Release. Detection and Verification System (DDVS) expands the Flat Surface Damage Detection System (FSDDS) sensory panels damage detection capabilities and includes an autonomous inspection capability utilizing cameras and dynamic computer vision algorithms to verify system health. Objectives of this formulation task are to establish the concept of operations, formulate the system requirements for a potential ISS flight experiment, and develop a preliminary design of an autonomous inspection capability system that will be demonstrated as a proof-of-concept ground based damage detection and inspection system.

Damage detection↗

Autonomous reinforcement learning agent for stretchable kirigami design of 2D materials

Abstract Mechanical behavior of 2D materials such as MoS 2 can be tuned by the ancient art of kirigami. Experiments and atomistic simulations show that 2D materials can be stretched more than 50% by strategic insertion of cuts. However, designing kirigami structures with desired mechanical properties is highly sensitive to the pattern and location of kirigami cuts. We use reinforcement learning (RL) to generate a wide range of highly stretchable MoS 2 kirigami structures. The RL agent is trained by a small fraction (1.45%) of molecular dynamics simulation data, randomly sampled from a search space of over 4 million candidates for MoS 2 kirigami structures with 6 cuts. After training, the RL agent not only proposes 6-cut kirigami structures that have stretchability above 45%, but also gains mechanistic insight to propose highly stretchable (above 40%) kirigami structures consisting of 8 and 10 cuts from a search space of billion candidates as zero-shot predictions.

36 MATERIALS SCIENCE↗

Design Requirements and Software Specification for the Autonomous Energy Management Software System for Small Commercial Buildings

Commercial buildings are responsible for approximately 20 percent of the total United States energy consumption and greenhouse gas emissions. Over 85 percent of these buildings lack building automation systems. Many of these buildings are small (<50,000 square feet), underserved, and use rooftop units for heating, ventilation, and air-conditioning needs. Because these buildings lack proper energy management systems, they have several operational deficiencies that lead to excess energy consumption. Studies have shown that managing the rooftop units heating and cooling set points, schedules, setbacks, and optimal start can result in 20 to 25 percent reduction in electricity consumption in small commercial buildings. In addition, improving demand flexibility of these buildings will result additional cost savings for the building owner. Therefore, the Department of Energy’s Building Technologies Office approved a project to address the needs for small commercial buildings. The project is led by Pacific Northwest National Laboratory (PNNL) with Intellimation LLC as the cooperative research and development agreement partner. The primary goal of the project is to develop and validate an autonomous energy management software (AEMS) system that will continuously optimize small commercial building operations by minimizing energy consumption and cost, while providing a solution for maximizing decarbonization benefits from electrification of buildings. The work will leverage the vast experience of PNNL research and development staff who have over two decades of experience in developing and successfully transferring software technologies to the private sector. This solution will be jointly developed with Intellimation, a company that plans to use it to scale their building energy efficiency (EE) and grid services offering. Widespread deployment of the AEMS system will improve the EE and demand flexibility of the building commercial building stock. It should also support cities and states in meeting their climate change mitigation goals. This document describes the various EE and grid service features of the AEMS system, infrastructure and data required to implement those features, and how the features should be automated. It also details how the various features will be tested and validated, including field validation. The document also details what flexibility the users have and how they will be able to leverage those capabilities exercise those. The intent is to create an AEMS system that would support scalable deployment, requires minimal configuration, and is easy to maintain over its expected lifespan. The initial alpha release of AEMS system is planned for March 2023, and the beta release is planned for the summer of 2023. The final release is planned for March 2024. Section 2 of the report documents the relevant building types that AEMS is suitable for. Section 3 documents EE features that will be supported. It will also include the data requirements, hardware requirements, implementation details, and how EE features will be tested and validated. Grid service features will be documented in section 4, including data requirements, hardware requirements, implementation details, and how the services will be tested and validated. Planned next steps are described in section 5.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗