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NASA NTRS2003

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.↗
NASA NTRS2016

Transitioning Autonomous Systems Technology Research to a Flight Software Environment

NASA has developed methods and algorithms for autonomous spacecraft operations,including automated planning and scheduling, fault diagnostics and impact determination,procedure management and display. Making the transition from technology research tooperational flight software requires overcoming significant technical, programmatic andcultural challenges. Technology research is aimed at developing methods that performspecific functions correctly, but the resulting software may not be designed for flightprocessors with limited CPU, memory and network resources, and may not be easilyintegrated into spacecraft flight software. Our objective in the Autonomous Systems andOperations Project is to make significant strides toward the transformation from technologyto operational use. Our focus was twofold: maturing research grade autonomy software intoa flight software environment using broadly accepted languages and tools; and integratingautonomy applications with each other and with representative systems and their data andcommand interfaces. For a target flight software environment, we chose Core FlightSoftware, developed by Goddard Space Flight Center as a common operating systemindependent framework. Our hardware integration environment was provided by theIntegrated Power and Avionics Systems (iPAS) Lab at Johnson Space Center, in whichvarious subsystem development has been conducted to address engineering challenges forthe vehicles and systems required for long-duration missions into the solar system. The iPASand its network of connected facilities provides realistic subsystem hardware or simulationsof spacecraft power, life support, guidance, navigation and control, and command and datahandling subsystems. Interfaces between autonomy applications and the subsystems beingassessed and controlled were developed, assessed and refined. The hardware and softwareenvironment using CFS and the iPAS facility has proven to be a highly flexible and realisticenvironment in which to rapidly integrate applications in an iterative, low cost setting. Usingthe integration environment we have developed, we will turn our focus to performance andsizing analysis to determine the computational requirements for full-scale deployment ofautonomy technology. Scalability of reasoners and the spacecraft models upon which theyoperate, and robustness across the full range of spacecraft conditions and environments willbe explored and improved. We are making significant contributions to the future programsthat will build the spacecraft that will take humans beyond the Earth-Moon system, in whichprogram Systems Engineers will be able to accurately and confidently design in accurate,robust and mature autonomous operations systems.

Flight Software↗
NASA NTRS2006

AERCam Autonomy: Intelligent Software Architecture for Robotic Free Flying Nanosatellite Inspection Vehicles

The NASA Johnson Space Center has developed a nanosatellite-class Free Flyer intended for future external inspection and remote viewing of human spacecraft. The Miniature Autonomous Extravehicular Robotic Camera (Mini AERCam) technology demonstration unit has been integrated into the approximate form and function of a flight system. The spherical Mini AERCam Free Flyer is 7.5 inches in diameter and weighs approximately 10 pounds, yet it incorporates significant additional capabilities compared to the 35-pound, 14-inch diameter AERCam Sprint that flew as a Shuttle flight experiment in 1997. Mini AERCam hosts a full suite of miniaturized avionics, instrumentation, communications, navigation, power, propulsion, and imaging subsystems, including digital video cameras and a high resolution still image camera. The vehicle is designed for either remotely piloted operations or supervised autonomous operations, including automatic stationkeeping, point-to-point maneuvering, and waypoint tracking. The Mini AERCam Free Flyer is accompanied by a sophisticated control station for command and control, as well as a docking system for automated deployment, docking, and recharge at a parent spacecraft. Free Flyer functional testing has been conducted successfully on both an airbearing table and in a six-degree-of-freedom closed-loop orbital simulation with avionics hardware in the loop. Mini AERCam aims to provide beneficial on-orbit views that cannot be obtained from fixed cameras, cameras on robotic manipulators, or cameras carried by crewmembers during extravehicular activities (EVA s). On Shuttle or International Space Station (ISS), for example, Mini AERCam could support external robotic operations by supplying orthogonal views to the intravehicular activity (IVA) robotic operator, supply views of EVA operations to IVA and/or ground crews monitoring the EVA, and carry out independent visual inspections of areas of interest around the spacecraft. To enable these future benefits with minimal impact on IVA operators and ground controllers, the Mini AERCam system architecture incorporates intelligent systems attributes that support various autonomous capabilities. 1) A robust command sequencer enables task-level command scripting. Command scripting is employed for operations such as automatic inspection scans over a region of interest, and operator-hands-off automated docking. 2) A system manager built on the same expert-system software as the command sequencer provides detection and smart-response capability for potential system-level anomalies, like loss of communications between the Free Flyer and control station. 3) An AERCam dynamics manager provides nominal and off-nominal management of guidance, navigation, and control (GN&C) functions. It is employed for safe trajectory monitoring, contingency maneuvering, and related roles. This paper will describe these architectural components of Mini AERCam autonomy, as well as the interaction of these elements with a human operator during supervised autonomous control.

Fredrickson, Steven E.↗
NASA NTRSDate not supplied

Earth Independent Medical Operations (EIMO)

Inherent in interplanetary space travel are unprecedented challenges that could threaten mission success and negatively impact crew health and performance. Return to definitive care is essentially untenable and resources will be constrained with practically no re-supply capability. Access to ground-based medical expertise will be significantly delayed under nominal conditions with exacerbation during conjunction or prolonged dust storms. Taken together, these challenges necessitate the development of a progressively autonomous medical operational support system to assist the crew medical officer (CMO). While support from ground based medical experts will remain indispensable for pre-mission planning, the approach to management of acute/emergent medical contingencies will require a gradual transition of medical care and decision making from terrestrial to space-based assets, enabling support of astronaut health and performance and reducing overall mission risk. To progressively enable EIMO, a series of meetings were convened with subject matter experts from within NASA, academia and industry to facilitate mapping of the path to support autonomous medical operations. Topics explored in these meetings included the scope of data (storage capacity, usage, transmission rate and bandwidth, computing capacity), CMO training, supply and resource management and task load balance. Recommendations from these meetings will inform the EIMO Concept of Operations and definition of the associated requirements culminating in updates to the NASA 3001 standards. The EIMO project team will work with stakeholders to conceptualize a clinical decision support system (CDSS) to assist the CMO in response to medical contingencies when terrestrial support is delayed or otherwise unavailable. The CDSS will be a system of systems that will utilize data from numerous input vectors. Successful deployment of the CDSS will facilitate medical decision making while decreasing the cognitive load leading to an improvement in task load balancing. Additional benefits of the envisioned CDSS include assistance with inventory management, locating resources, storage/retrieval of medical records, highlighting trends in recorded data, in addition to providing a consult for diagnosis and treatment. More advanced features might include passive monitoring to identify early warning signs of behavioral or medical anomalies to possibly pre-empt onset of conditions that would compromise crew health and performance.

Benjamin Easter↗
NASA NTRSDate not supplied

A Structurally-Adaptive Framework for Distributed Airborne Sensing over Real-time Collaborative Information Sharing Networks

The emergence and maturation of wireless communication technologies continue to transform the aviation industry and are enabling new solutions to challenges faced by NASA’s Advanced Air Mobility (AAM) initiative. AAM is leading towards high-density autonomous aircraft operations in areas underserved by traditional aviation, such as over densely populated urban centers. In this paper, we build on concepts from Smart Spaces - where sensing, processing, and communication are embedded in an environment, and agents are operating within the space can exploit these capabilities in real-time through collaborative information sharing networks. Building from these concepts, we propose a framework to enable a dynamic, topologically-adaptive, and distributed estimation system for man-rated aviation to address challenges faced by autonomous AAM operations. This paper presents the initial concept of operations and system design for this framework, presents a mathematical formulation for abstraction of the problem, identifies requirements and constraints for operation, and presents algorithmic constructs and mathematical formalisms to demonstrate operation. The proposed framework will be evaluated on a regional AAM flight scenario and will focus on two initial applications: (1) GPS-free navigation supporting precision approach and landing (PAL), and (2) surveillance and conformance monitoring of aircraft in vertiport airspaces. Such approaches show promise in addressing gaps in current technologies needed to enable future AAM concepts, while promising greater capabilities, performance, robustness, and safety over current aviation systems and operations.

Structurally-Adaptive↗
NASA NTRSDate not supplied

A Structurally-Adaptive Framework for Distributed Airborne Sensing over Real-time Collaborative Information Sharing Networks

The emergence and maturation of wireless communication technologies continue to transform the aviation industry and are enabling new solutions to challenges faced by NASA’s Advanced Air Mobility (AAM) initiative. AAM is leading towards high-density autonomous aircraft operations in areas underserved by traditional aviation, such as over densely populated urban centers. In this paper, we build on concepts from distributed sensing and smart spaces - where sensing, processing, and communication are embedded in an environment, and agents are operating within the space can exploit these capabilities in real-time through collaborative information sharing networks. Building from these concepts, we propose a framework to enable a dynamic, topologically-adaptive, and distributed estimation system for man-rated aviation to address challenges faced by autonomous AAM operations. This paper presents the initial concept of operations and system design for this framework, presents a mathematical formulation for abstraction of the problem, identifies requirements and constraints for operation, and presents algorithmic constructs to demonstrate operation. The initial framework design will focus on supporting precision navigation and independent surveillance supporting conformance monitoring of aircraft in airspace corridors and vertiport airspaces. Preliminary results from this framework shows promise in addressing gaps in current technologies needed to enable future AAM concepts, while promising greater capabilities, performance, robustness, and safety over current aviation systems and operations.

Distributed sensing↗
NASA NTRS2010

Secure Autonomous Automated Scheduling (SAAS)

This report describes network-centric operations, where a virtual mission operations center autonomously receives sensor triggers, and schedules space and ground assets using Internet-based technologies and service-oriented architectures. For proof-of-concept purposes, sensor triggers are received from the United States Geological Survey (USGS) to determine targets for space-based sensors. The Surrey Satellite Technology Limited (SSTL) Disaster Monitoring Constellation satellite, the UK-DMC, is used as the space-based sensor. The UK-DMC's availability is determined via machine-to-machine communications using SSTL's mission planning system. Access to/from the UK-DMC for tasking and sensor data is via SSTL's and Universal Space Network's (USN) ground assets. The availability and scheduling of USN's assets can also be performed autonomously via machine-to-machine communications. All communication, both on the ground and between ground and space, uses open Internet standards

Walke, Jon G.↗
NASA NTRS2009

Surface Habitat Systems

The Surface Habitat Systems (SHS) Focused Investment Group (FIG) is part of the National Aeronautics and Space Administration (NASA) Johnson Space Center (JSC) effort to provide a focused direction and funding to the various projects that are working on human surface habitat designs and technologies for the planetary exploration missions. The overall SHS-FIG effort focuses on directing and guiding those projects that: 1) develop and demonstrate new surface habitat system concepts, innovations, and technologies to support human exploration missions, 2) improve environmental systems that interact with human habitats, 3) handle and emplace human surface habitats, and 4) focus on supporting humans living and working in habitats on planetary surfaces. The activity areas of the SHS FIG described herein are focused on the surface habitat project near-term objectives as described in this document. The SHS-FIG effort focuses on mitigating surface habitat risks (as identified by the Lunar Surface Systems Project Office (LSSPO) Surface Habitat Element Team; and concentrates on developing surface habitat technologies as identified in the FY08 gap analysis. The surface habitat gap assessment will be updated annually as the surface architecture and surface habitat definition continues to mature. These technologies are mapped to the SHS-FIG Strategic Development Roadmap. The Roadmap will bring to light the areas where additional innovative efforts are needed to support the development of habitat concepts and designs and the development of new technologies to support of the LSSPO Habitation Element development plan. Three specific areas of development that address Lunar Architecture Team (LAT)-2 and Constellation Architecture Team (CxAT) Lunar habitat design issues or risks will be focused on by the SHS-FIG. The SHS-FIG will establish four areas of development that will help the projects prepare in their planning for surface habitat systems development. Those development areas are the 1) surface habitat concept definition, 2) inflatable surface habitat development, and 3) autonomous habitat operations, and 4) cross-cutting / systems engineering. In subsequent years, the SHS-FIG will solicit a call for innovations and technologies that will support the development of these four development areas. The other development areas will be assessed yearly and identified on the SHS-FIG s Strategic Development Roadmap. Initial investment projects that are funded by the Constellation Program Office (CxPO), LSSPO, or the Exploration Technology Development Projects (ETDP) will also be included on the Roadmap. For example, in one or two years from now, the autonomous habitat operations and testbed would collaborations with the Integrated Systems Health Management (ISHM) and Automation for Operations ETDP projects, which will give the surface habitat projects an integrated habitat autonomy testbed to test software and systems. The SHS-FIG scope is to provide focused direction for multiple innovations, technologies and subsystems that are needed to support humans at a remote planetary surface habitat during the concept development, design definition, and integration phases of that project. Subsystems include: habitability, lightweight structures, power management, communications, autonomy, deployment, outfitting, life support, wireless connectivity, lighting, thermal and more.

Kennedy, Kriss J.↗
NASA NTRS2017

Progress of Crew Autonomous Scheduling Test (CAST) On the ISS

The United States space policy is evolving toward missions beyond low Earth orbit. In an effort to meet that policy, NASA has recognized Autonomous Mission Operations (AMO) as a valuable capability. Identified within AMO capabilities is the potential for autonomous planning and replanning during human spaceflight operations. That is allowing crew members to collectively or individually participate in the development of their own schedules. Currently, dedicated mission operations planners collaborate with international partners to create daily plans for astronauts aboard the International Space Station (ISS), taking into account mission requirements, ground rules, and various vehicle and payload constraints. In future deep space operations the crew will require more independence from ground support due to communication transmission delays. Furthermore, crew members who are provided with the capability to schedule their own activities are able to leverage direct experience operating in the space environment, and possibly maximize their efficiency. CAST (Crew Autonomous Scheduling Test) is an ISS investigation designed to analyze three important hypotheses about crew autonomous scheduling. First, given appropriate inputs, the crew is able to create and execute a plan in a reasonable period of time without impacts to mission success. Second, the proximity of the planner, in this case the crew, to the planned operations increases their operational efficiency. Third, crew members are more satisfied when given a role in plan development. This presentation shows the progress done in this study with a single astronaut test subject participating in five CAST sessions. CAST is a technology demonstration payload sponsored by the ISS Research Science and Technology Office, and performed by experts in Mission Operations Planning from the Flight Operations Directorate at NASA Johnson Space Center, and researchers across multiple NASA centers.

Healy, Matthew↗
NASA NTRS2020

Robotic Assembly Activities at NASA Langley Research Center

Over the past several decades, NASA Langley Research Center (LaRC) has developed a suite of hardware and software capabilities for robotic in-space assembly. Specific robots include the Lightweight Surface Manipulation System (LSMS), Tendon-Actuated Lightweight In-Space Manipulator (TALISMAN), NASA Intelligent Jigging and Assembly Robot (NINJAR), Strut Assembly, Manufacturing, Utility & Robotic Aid (SAMURAI), and most recently the Assemblers modular robots. Alongside the hardware, software tools such as the Autonomous Entity Operations Network (AEON) and the Baseline Environment for Autonomous Modeling (BEAM) have been developed to enable communication and simulation respectively. These tools have supported foundational research in single and multi-agent control, sensing and perception, trajectory generation, task allocation, and human-machine teaming. This talk will provide a broad overview of these capabilities and go into detail on recent developments made by the Assemblers project to create modular, reconfigurable robots for autonomous in-space assembly.

John R Cooper↗
NASA NTRS2009

A Conceptual Study for the Autonomous Direct Forming of Lunar Regolith into Flexlock (Trademark) Geomats for Lunar Surface Operations

We describe the conceptual method of an autonomously operable Direct Forming machine that would consume regolith or regolith slag to mold intimately, interlinked elements in a continuous process. The resulting product, one to three meter wide geomats, would be deployed over commonly traversed areas to isolate the astronauts and equipment from underlying dust. The porous geotextile would provide areas for dust settling, thereby mitigating dust impingement on astronaut suits or surface structures. Because of their self-supporting yet flexible structure, these geomats could be assembled into shields and buttresses to protect lunar habitants from radiation, forming a "flexoskeleton" from in situ materials.

Robertson, Luke B.↗
NASA NTRSDate not supplied

Demonstration of Two Extended Visual Line of Sight Methods for Urban UAV Operations

This report describes two extended visual line of sight (EVLOS) methods developed and utilized during two flight campaigns over the campus of NASA Langley Research Center (LaRC): a chase vehicle method and a radio controlled (RC) pilot handoff method. These campaigns were performed to (a) evaluate small unmanned aerial system (sUAS) flight beyond the visual line of sight (BVLOS) of the ground control station operator and (b) test technologies under development to enable a transition from EVLOS to BVLOS operations. While an autonomous waypoint-based operational approach enabled minimal pilot intervention in both methods, range containment was enforced (a) manually via continual pilot visual monitoring and (b) autonomously via on-board contingency landing autonomy triggerable at the boundary of stay-in geofences. In the thirty-nine flights which utilized the chase vehicle, the pilot followed the sUAS flying a 1.2 km path at 40m altitude over urban streets. In the fifteen flights which utilized pilot handoff, a pilot at one end of a 1.5 km path initiated the flight at 120m altitude over buildings and trees, and at the midway point of the path transferred radio control to a pilot at the other end. In comparison, the chase vehicle method requires less ground crew and simpler avionics, while the pilot handoff method avoids schedule risk arising from street traffic congestion but better replicates actual direct routing for BVLOS flights. Collision risk with another aircraft was introduced in both campaigns and mitigated with the same manual and autonomous methods. Results from these campaigns serve as a basis for planned BVLOS operations at NASA LaRC.

Nicholas Rymer↗
NASA NTRS2019

A Control Framework for Autonomous Smart Grids for Space Power Applications

With the National Aeronautics and Space Administration's (NASA) rising interest in lunar surface operations and deep space exploration, there is a growing need to move from traditional ground-based mission operations to more autonomous vehicle level operations. In lunar surface operations, there are periods of time where communications with ground-based mission control could not occur, forcing vehicles and a lunar base to completely operate independent of the ground. For deep space exploration missions, communication latency times increase to greater than 15 minutes making real-time control of critical systems difficult, if not near impossible. These challenges are driving the need for an autonomous power control system that has the capability to manage power and energy. This will ensure that critical loads have the necessary power to support life systems and carry out critical mission objectives. This paper presents a flexible, hierarchical, distributed control methodology that enables autonomous operation of smart grids and can integrate into a higher level autonomous architecture.

Csank, Jeffrey T.↗