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NASA NTRS2022

Science Autonomy for Ocean Worlds Astrobiology: A Perspective

Astrobiology missions to ocean worlds in our solar system must overcome both scientific and technological challenges due to extreme temperature and radiation conditions, long communication times, and limited bandwidth. While such tools could not replace ground-based analysis by science and engineering teams, machine learning algorithms could enhance the science return of these missions through development of autonomous science capabilities. Examples of science autonomy include onboard data analysis and subsequent instrument optimization, data prioritization (for transmission), and real-time decision-making based on data analysis. Similar advances could be made to develop streamlined data processing software for rapid ground-based analyses. Here we discuss several ways machine learning and autonomy could be used for astrobiology missions, including landing site selection, prioritization and targeting of samples, classification of “features” (e.g., proposed biosignatures) and novelties (uncharacterized, “new” features, which may be of most interest to agnostic astrobiological investigations), and data transmission.

ocean worlds↗
NASA NTRS2004

Software for Intelligent System Health Management

This viewgraph presentation describes the characteristics and advantages of autonomy and artificial intelligence in systems health monitoring. The presentation lists technologies relevant to Intelligent System Health Management (ISHM), and some potential applications.

Trevino, Luis C.↗
NASA NTRS2021

Case Studies in Verifying Spacecraft Autonomy

Spacecraft, operating with a time-to-effect faster than human command response, or with absent or delayed communication, have depended on autonomy. It is likely that this reliance will continue, and increase further in future missions. Spacecraft autonomy is used when operator intervention is not available or feasible, or when dynamic aspects of a spacecraft situation cannot be predicted in advance. This paper provides case studies of several successfully verified autonomous software systems across multiple spacecraft, flight phases (launch, transit, entry and landing, science utilization), and software classifications, and can serve as examples to future missions in methods of successfully assuring spacecraft autonomy.

Johnson, Stephen B.↗
NASA NTRS2005

Investigation of Integrated Vehicle Health Management Approaches

This report is to present the work that was performed during the summer in the Advance Computing Application office. The NFFP (NASA Faculty Fellow Program) had ten summer faculty members working on IVHM (Integrated Vehicle Health Management) technologies. The objective of this project was two-fold: 1) to become familiar with IVHM concepts and key demonstrated IVHM technologies; and 2) to integrate the research that has been performed by IVHM faculty members into the MASTLAB (Marshall Avionic Software Test Lab). IVHM is a NASA-wide effort to coordinate, integrate and apply advanced software, sensors and design technologies to increase the level of intelligence, autonomy, and health state of future vehicles. IVHM is an important concept because it is consistent with the current plan for NASA to go to the moon, mars, and beyond. In order for NASA to become more involved in deep exploration, avionic systems will need to be highly adaptable and autonomous.

Paris, Deidre↗
NASA NTRS2004

The TechSat 21 Autonomous Sciencecraft Experiment

Software has been developed to perform a number of functions essential to autonomous operation in the Autonomous Sciencecraft Experiment (ASE), which is scheduled to be demonstrated aboard a constellation of three spacecraft, denoted TechSat 21, to be launched by the Air Force into orbit around the Earth in January 2006. A prior version of this software was reported in Software for an Autonomous Constellation of Satellites (NPO-30355), NASA Tech Briefs, Vol. 26, No. 11 (November 2002), page 44. The software includes the following components: Algorithms to analyze image data, generate scientific data products, and detect conditions, features, and events of potential scientific interest; A program that uses component-based computational models of hardware to analyze anomalous situations and to generate novel command sequences, including (when possible) commands to repair components diagnosed as faulty; A robust-execution-management component that uses the Spacecraft Command Language (SCL) software to enable event-driven processing and low-level autonomy; and The Continuous Activity Scheduling, Planning, Execution, and Replanning (CASPER) program for replanning activities, including downlink sessions, on the basis of scientific observations performed during previous orbit cycles.

Sherwood, Robert↗
NASA NTRS2008

Improved CLARAty Functional-Layer/Decision-Layer Interface

Improved interface software for communication between the CLARAty Decision and Functional layers has been developed. [The Coupled Layer Architecture for Robotics Autonomy (CLARAty) was described in Coupled-Layer Robotics Architecture for Autonomy (NPO-21218), NASA Tech Briefs, Vol. 26, No. 12 (December 2002), page 48. To recapitulate: the CLARAty architecture was developed to improve the modularity of robotic software while tightening coupling between planning/execution and basic control subsystems. Whereas prior robotic software architectures typically contained three layers, the CLARAty contains two layers: a decision layer (DL) and a functional layer (FL).] Types of communication supported by the present software include sending commands from DL modules to FL modules and sending data updates from FL modules to DL modules. The present software supplants prior interface software that had little error-checking capability, supported data parameters in string form only, supported commanding at only one level of the FL, and supported only limited updates of the state of the robot. The present software offers strong error checking, and supports complex data structures and commanding at multiple levels of the FL, and relative to the prior software, offers a much wider spectrum of state-update capabilities.

Estlin, Tara↗
NASA NTRSDate not supplied

Trustworthy Autonomy for Gateway Vehicle System Manager

The Vehicle System Manager (VSM) is the highest-level software control system in the Gateway hierarchical Autonomous System Management Architecture. The VSM provides four function categories: Mission Management and Timeline Execution, Resource Management, Fault Management, Vehicle Control and Operation. VSM provides various levels of automation ranging from fully autonomous operations with no flight crew and minimal ground monitoring to advisory automation when Gateway is crewed and has full ground monitoring. Trustworthiness is achieved via verified specification, comprehensive development verification, and real-time verification using assume-guarantee contracts. Development verification includes semantic verification of the data model via peer review and testing and assume-guarantee contracts implemented using the PlusCal/TLA+ environment. VSM also uses runtime assume-guarantee contracts, implemented in R2U2 via a runtime monitor that feeds the necessary telemetry data to R2U2 and which receives and responds to the R2U2 verdict stream. The full lifecycle verification approach and use of assume-guarantee contracts provides increased trustworthiness to VSM. Preliminary results provide encouragement that VSM can be both autonomous and trustworthy.

Assume-guarantee contracts↗
NASA NTRSDate not supplied

Mars Ascent Vehicle GNC Targeting Routines with Considerations for Flight Software Development

The Mars Ascent Vehicle (MAV) will be the first vehicle to perform an ascent from the surface of another atmospheric planetary body outside of the Earth-Moon system. Significant light-time delay requires complete autonomy of flight throughout ascent, and naturally a high level of reliability is desired in both MAV’s hardware and software subsystems. The MAV Guidance, Navigation and Controls (GNC) team and the MAV Flight Software (FSW) team have partnered together to improve the efficiency of algorithm integration onto the MAV flight processor, and to increase confidence that said integration is successful and without human error. An interface architecture is proposed for the GNC suite that allows both the guidance and navigation subsystems to provide code algorithms directly in C++, and the controls subsystem to provide MATLAB Simulink auto-coded algorithms. Several continuous integration/deployment (CI/CD) methodologies have been considered for ease of transition of algorithm code from the GNC team to the FSW team. The GNC/FSW teams also worked together to develop a cFS-friendly wrapper which abstracts the integration of the GNC algorithm code into an interface-level API that is compatible with cFS. Several iterations of vehicle GNC code have been produced between the GNC/FSW team’s partnership, and this strong interface between these two teams have allowed the GNC/FSW teams to greatly increase confidence of efficient and error-free implementation of the GNC code onto MAV for a successful flight.

Jason Everett↗
NASA NTRSDate not supplied

Promoting Crew Autonomy in a Human Spaceflight Earth Analog Mission through Self-Scheduling

Deep space exploration missions face the challenge of communication transmission latencies between ground stations and astronaut crews due to increasing distance between the Earth and spacecraft in transit. To address this, research at NASA has aimed toward supporting crew autonomy by enabling astronauts to schedule their own timelines with minimal oversight from Mission Control. While self-scheduling has been shown to be feasible, it is yet to be studied as an integral part of autonomous crew operations. The current paper reviews the operationalization of self-scheduling and a number of related objectives during Campaign 6 of HERA, a Human Exploration Research Analog. Research objectives include studying the effects of phasic autonomy over the course of a 45-day mission, evaluating differences in scheduling performance produced by software interface aids, and deploying a novel measure of crew attitudes toward self-scheduling and plan execution.

crew autonomy↗
NASA NTRSDate not supplied

Promoting Crew Autonomy in a Human Spaceflight Earth Analog Mission through Self-Scheduling

Deep space exploration missions face the challenge of communication transmission latencies between ground stations and astronaut crews due to increasing distance between the Earth and spacecraft in transit. To address this, research at NASA has aimed toward supporting crew autonomy by enabling astronauts to schedule their own timelines with minimal oversight from Mission Control. While self-scheduling has been shown to be feasible, it is yet to be studied as an integral part of autonomous crew operations. The current paper reviews the operationalization of self-scheduling and a number of related objectives during Campaign 6 of HERA, a Human Exploration Research Analog. Research objectives include studying the effects of phasic autonomy over the course of a 45-day mission, evaluating differences in scheduling performance produced by software interface aids, and deploying a novel measure of crew attitudes toward self-scheduling and plan execution.

crew autonomy↗
NASA NTRSDate not supplied

Software Design for the Supervised Autonomous Assembly of a Tall Lunar Tower

Tall towers enable a wide-ranging set of capabilities on the lunar surface including communication, navigation, surveillance, power generation, and more. The Tall Lunar Tower project at NASA Langley Research Center is focused on the design, modeling, fabrication, and testing of an engineering development unit to assemble a tall tower through supervised autonomous operations. In this paper, the software design for the supervised autonomous assembly of a tall lunar tower is presented. The paper includes a high-level description of the concept of operations, the agents, and an overview of the software architecture.

Moon↗
NASA NTRS2017

Medical Systems Engineering to Support Mars Mission Crew Autonomy

Human spaceflight missions to Mars face exceptionally challenging resource limitations that far exceed those faced before. Increasing transit times, decreasing opportunity for resupply, communications challenges, and extended time to evacuate a crew to definitive medical care dictate a level of crew autonomy in medical care that is beyond the current medical model. To approach this challenge, a medical systems engineering approach is proposed that relies on a clearly articulated Concept of Operations and risk analysis tools that are in development at NASA. This paper proposes an operational clinical model with key terminology and concepts translated to a controls theory paradigm to frame a common language between clinical and engineering teams. This common language will be used for design and validation of an exploration medical system that is fully integrated into a Mars transit vehicle. This approach merges medical simulation, human factors evaluation techniques, and human-in-the-loop testing in ground based analogs to tie medical hardware and software subsystem performance and overall medical system functionality to metrics of operational medical autonomy. Merging increases in operational clinical autonomy with a more restricted vehicle system resource scenario in interplanetary spaceflight will require an unprecedented level of medical and engineering integration. Full integration of medical capabilities into a Mars vehicle system may require a new approach to integrating medical system design and operations into the vehicle Program structure. Prior to the standing-up of a Mars Mission Program, proof of concept is proposed through the Human Research Program.

Antonsen, Erik↗
NASA NTRS2001

Collaboration Between NASA Centers of Excellence on Autonomous System Software Development

Software for space systems flight operations has its roots in the early days of the space program when computer systems were incapable of supporting highly complex and flexible control logic. Control systems relied on fast data acquisition and supervisory control from a roomful of systems engineers on the ground. Even though computer hardware and software has become many orders of magnitude more capable, space systems have largely adhered to this original paradigm In an effort to break this mold, Kennedy Space Center (KSC) has invested in the development of model-based diagnosis and control applications for ten years having broad experience in both ground and spacecraft systems and software. KSC has now partnered with Ames Research Center (ARC), NASA's Center of Excellence in Information Technology, to create a new paradigm for the control of dynamic space systems. ARC has developed model-based diagnosis and intelligent planning software that enables spacecraft to handle most routine problems automatically and allocate resources in a flexible way to realize mission objectives. ARC demonstrated the utility of onboard diagnosis and planning with an experiment aboard Deep Space I in 1999. This paper highlights the software control system collaboration between KSC and ARC. KSC has developed a Mars In-situ Resource Utilization testbed based on the Reverse Water Gas Shift (RWGS) reaction. This plant, built in KSC's Applied Chemistry Laboratory, is capable of producing the large amount of Oxygen that would be needed to support a Human Mars Mission. KSC and ARC are cooperating to develop an autonomous, fault-tolerant control system for RWGS to meet the need for autonomy on deep space missions. The paper will also describe how the new system software paradigm will be applied to Vehicle Health Monitoring, tested on the new X vehicles and integrated into future launch processing systems.

Goodrich, Charles H.↗
NASA NTRS1993

International testing of a Mars rover prototype

Tests on a prototype engineering model of the Russian Mars 96 Rover were conducted by an international team in and near Death Valley in the United States in late May, 1992. These tests were part of a comprehensive design and testing program initiated by the three Russian groups responsible for the rover development. The specific objectives of the May tests were: (1) evaluate rover performance over different Mars-like terrains; (2) evaluate state-of-the-art teleoperation and autonomy development for Mars rover command, control and navigation; and (3) organize an international team to contribute expertise and capability on the rover development for the flight project. The range and performance that can be planned for the Mars mission is dependent on the degree of autonomy that will be possible to implement on the mission. Current plans are for limited autonomy, with Earth-based teleoperation for the nominal navigation system. Several types of television systems are being investigated for inclusion in the navigation system including panoramic camera, stereo, and framing cameras. The tests used each of these in teleoperation experiments. Experiments were included to consider use of such TV data in autonomy algorithms. Image processing and some aspects of closed-loop control software were also tested. A micro-rover was tested to help consider the value of such a device as a payload supplement to the main rover. The concept is for the micro-rover to serve like a mobile hand, with its own sensors including a television camera.

Kemurjian, Alexsandr Leonovich↗
NASA NTRS2014

Software Engineering for Human Spaceflight

The Spacecraft Software Engineering Branch of NASA Johnson Space Center (JSC) provides world‐class products, leadership, and technical expertise in software engineering, processes, technology, and systems management for human spaceflight. The branch contributes to major NASA programs (e.g. ISS, MPCV/Orion) with in‐house software development and prime contractor oversight, and maintains the JSC Engineering Directorate CMMI rating for flight software development. Software engineering teams work with hardware developers, mission planners, and system operators to integrate flight vehicles, habitats, robotics, and other spacecraft elements. They seek to infuse automation and autonomy into missions, and apply new technologies to flight processor and computational architectures. This presentation will provide an overview of key software‐related projects, software methodologies and tools, and technology pursuits of interest to the JSC Spacecraft Software Engineering Branch.

Fredrickson, Steven E.↗
NASA NTRS2023

An Overview of Distributed Spacecraft Autonomy at NASA Ames

Autonomous decision-making significantly increases mission effectiveness by mitigating the effects of communication constraints, like latency and bandwidth, and mission complexity on multi-spacecraft operations. To advance the state of the art in autonomous Distributed Space Systems (DSS), the Distributed Spacecraft Autonomy (DSA) team at NASA's Ames Research Center is developing within five relevant technical areas: distributed resource and task management, reactive operations, system modeling and simulation, human-swarm interaction, and ad hoc network communications. DSA is maturing these technologies - critical for future large autonomous DSS - from concept to launch via simulation studies and orbital deployments. A 100-node heterogenous Processor-in-the-Loop (PiL) testbed aids distributed autonomy capability development and verification of multi-spacecraft missions. The DSA software payload deployed to the D-Orbit SCV-004 spacecraft demonstrates multi-agent reconfigurability and reliability as part of an ESA-sponsored in-orbit technology demonstration. Finally, DSA's primary flight mission showcases collaborative resource allocation for multipoint science data collection with four small spacecraft as a payload on NASA's Starling 1.0 satellites.

Caleb Ashmore Adams↗