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At least 19 records

Reliability-Aware Requirements Development for Autonomy Software

Autonomy is the ability of a system to make decisions and take actions in the presence of uncertainty. Validating autonomy, therefore, is a matter of validating that the system makes intelligent decisions even when there might be discrepancies between the observed and the expected state of the world as well as when the possible outcome of each of the possible courses of action is uncertain. During the requirements engineering phase, the functions, including those that are required to be autonomous and their expected behavior are specified. However, in the case of autonomous software system, it is challenging to specify all possible scenarios that the software may encounter. Additionally, since autonomous behaviors cannot always be fully predetermined, it is difficult to reason about their completeness and correctness. While these challenges are also faced with non-autonomous system, they are more prevalent for autonomous system due to their complexity and emergent behavior. Our efforts have been three-fold. On one hand, we have developed a goal-based method for requirements decomposition. We have embedded this approach into a higher-level systems engineering framework and then developed methods for decision and reliability analysis within this framework. And finally, we use simulation analysis to validate the more theoretical methods and provide a feedback mechanism. The decision analysis approach (DA) helps in identifying and mitigating the run-time risks, by bringing to the forefront the uncertainties, decisions, interactions, and other factors that may cause autonomous software to make erroneous decisions. The DA framework is used to quantify, for each decision that the software can make, failure risk due to uncertainties. The information about the key decisions and circumstances that can cause autonomous system to make incorrect decisions are used to generate test scenarios to be run in a simulator to ensure that the system can handle error-prone circumstances. The results or outcomes from decisions, based on the simulated scenarios, can then be leveraged to further gain insight of the assured system. We combine a goal-based approach with simulation analysis to facilitate requirements development for autonomous systems and further provide a method for run-time systems level reliability considerations during the autonomous software development process. The DA and the reliability analysis methods provide a formalism for the consideration of uncertainty in the run time decision-making process for autonomous software. This formalism considers the uncertainty involved in the outcome of different courses of action, in terms of performance and cost, as well as a method to consider the system level reliability implications. System level reliability considerations for autonomous software decision making contribute to the satisfaction of the system level goals over the lifecycle of a given mission. We demonstrate our approach using a hypothetical rover path planning example. The requirements for our rover simulator are based on existing literature about Mars rovers and lessons learned from real world observations at JPL. The specifics of the autonomy design for the Mars rovers, that have not been previously cleared for external release, are not used for our demonstrations.

Lindvall, Mikael↗

Autonomy Software: V&V Challenges and Characteristics

The successful operation of unmanned air vehicles requires software with a high degree of autonomy. Only if high level functions can be carried out without human control and intervention, complex missions in a changing and potentially unknown environment can be carried out successfully. Autonomy software is highly mission and safety critical: failures, caused by flaws in the software cannot only jeopardize the mission, but could also endanger human life (e.g., a crash of an UAV in a densely populated area). Due to its large size, high complexity, and use of specialized algorithms (planner, constraint-solver, etc.), autonomy software poses specific challenges for its verification, validation, and certification. -- - we have carried out a survey among researchers aid scientists at NASA to study these issues. In this paper, we will present major results of this study, discussing the broad spectrum. of notions and characteristics of autonomy software and its challenges for design and development. A main focus of this survey was to evaluate verification and validation (V&V) issues and challenges, compared to the development of "traditional" safety-critical software. We will discuss important issues in V&V of autonomous software and advanced V&V tools which can help to mitigate software risks. Results of this survey will help to identify and understand safety concerns in autonomy software and will lead to improved strategies for mitigation of these risks.

Schumann, Johann↗

Risk considerations for autonomy software

This paper summarizes key findings related to methods for the risk considerations of autonomy software. Existing methods for Verification and Validation (V&V) of autonomy software are summarized and a method for the assurance of autonomy software is suggested and demonstrated on a command execution use case. Risk and reliability are defined in the context of autonomy and an approach for risk assessment of autonomy is presented using an example use case. Key insights regarding areas of uncertainty for autonomy are provided, along with a suggested architecture for the systematic consideration of reliability within the context of a given autonomous planner.

Meshkat, Leila↗

Autonomy software verification and validation might not be as hard as it seems

The verification and validation of autonomy software is widely believed to be a challenging unsolved problem. To a certain extent this is true, but in this paper I argue that the problem is not nearly as severe as seems to be widely perceived. many of the perceived hard problems in autonomy software V&V also exist for traditional software, and can be solved using many of the same methods and techniques used for traditional spacecraft software. In particular, the problem of intractably large state spaces exists for any non-trivial software system.

Gat, Erann↗

Verification and Validation of Autonomy Software at NASA

Autonomous software holds the promise of new operation possibilities, easier design and development and lower operating costs. However, as those system close control loops and arbitrate resources on board with specialized reasoning, the range of possible situations becomes very large and uncontrollable from the outside, making conventional scenario-based testing very inefficient. Analytic verification and validation (V&V) techniques, and model checking in particular, can provide significant help for designing autonomous systems in a more efficient and reliable manner, by providing a better coverage and allowing early error detection. This article discusses the general issue of V&V of autonomy software, with an emphasis towards model-based autonomy, model-checking techniques and concrete experiments at NASA.

Pecheur, Charles↗

Verification and Validation of Autonomy Software at NASA

Autonomous software holds the promise of new operation possibilities, easier design and development, and lower operating costs. However, as those system close control loops and arbitrate resources on-board with specialized reasoning, the range of possible situations becomes very large and uncontrollable from the outside, making conventional scenario-based testing very inefficient. Analytic verification and validation (V&V) techniques, and model checking in particular, can provide significant help for designing autonomous systems in a more efficient and reliable manner, by providing a better coverage and allowing early error detection. This article discusses the general issue of V&V of autonomy software, with an emphasis towards model-based autonomy, model-checking techniques, and concrete experiments at NASA.

Pecheur, Charles↗

Autonomy Software Architecture for LORAX (Life On ice Robotic Antarctic eXplorer)

LORAX is a robotic astrobiological study of the ice field surrounding the Carapace Nunatak near the Allan Hills in Antarctica. The study culminates in a l00km traverse, sampling the ice at various depths (from surface to 10cm) at over 100 sites to survey microbial ecology and to record environmental parameters. The autonomy requirements from LORAX are shared by many robotic exploration tasks. Consequently, the LORAX autonomy architecture is a general architecture for on-board planning and execution in environments where science return is to be maximized against resource limitations and other constraints.

Jonsson, Ari↗

Mission Simulation Toolkit

The Mission Simulation Toolkit (MST) is a flexible software system for autonomy research. It was developed as part of the Mission Simulation Facility (MSF) project that was started in 2001 to facilitate the development of autonomous planetary robotic missions. Autonomy is a key enabling factor for robotic exploration. There has been a large gap between autonomy software (at the research level), and software that is ready for insertion into near-term space missions. The MST bridges this gap by providing a simulation framework and a suite of tools for supporting research and maturation of autonomy. MST uses a distributed framework based on the High Level Architecture (HLA) standard. A key feature of the MST framework is the ability to plug in new models to replace existing ones with the same services. This enables significant simulation flexibility, particularly the mixing and control of fidelity level. In addition, the MST provides automatic code generation from robot interfaces defined with the Unified Modeling Language (UML), methods for maintaining synchronization across distributed simulation systems, XML-based robot description, and an environment server. Finally, the MSF supports a number of third-party products including dynamic models and terrain databases. Although the communication objects and some of the simulation components that are provided with this toolkit are specifically designed for terrestrial surface rovers, the MST can be applied to any other domain, such as aerial, aquatic, or space.

Pisaich, Gregory↗

A Facility and Architecture for Autonomy Research

Autonomy is a key enabling factor in the advancement of the remote robotic exploration. There is currently a large gap between autonomy software at the research level and software that is ready for insertion into near-term space missions. The Mission Simulation Facility (MST) will bridge this gap by providing a simulation framework and suite of simulation tools to support research in autonomy for remote exploration. This system will allow developers of autonomy software to test their models in a high-fidelity simulation and evaluate their system's performance against a set of integrated, standardized simulations. The Mission Simulation ToolKit (MST) uses a distributed architecture with a communication layer that is built on top of the standardized High Level Architecture (HLA). This architecture enables the use of existing high fidelity models, allows mixing simulation components from various computing platforms and enforces the use of a standardized high-level interface among components. The components needed to achieve a realistic simulation can be grouped into four categories: environment generation (terrain, environmental features), robotic platform behavior (robot dynamics), instrument models (camera/spectrometer/etc.), and data analysis. The MST will provide basic components in these areas but allows users to plug-in easily any refined model by means of a communication protocol. Finally, a description file defines the robot and environment parameters for easy configuration and ensures that all the simulation models share the same information.

Pisanich, Greg↗

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.↗

"Reducing Detailed Vehicle Energy Dynamics to Physics-Like Models"

The energy demand of vehicles, particularly in unsteady drive cycles, is affected by complex dynamics internal to the engine and other powertrain components. Yet, in many applications, particularly macroscopic traffic flow modeling and optimization, structurally simple approximations to the complex vehicle dynamics are needed that nevertheless reproduce the correct effective energy behavior. This work presents a systematic model reduction pipeline that starts from complex vehicle models based on the Autonomie software and derives a hierarchy of simplified models that are fast to evaluate, easy to disseminate in open-source frameworks, and compatible with optimization frameworks. The pipeline, based on a virtual chassis dynamometer and subsequent approximation strategies, is reproducible and is applied to six different vehicle classes to produce concrete explicit energy models that represent an average vehicle in each class and leverage the accuracy and validation work of the Autonomie software.

Khoudari, Nour↗

Designing Autonomy into Interfaces for Long-Duration Missions

As NASA develops technologies for long-duration crewed missions, we must understand how communication between ground control teams and astronauts differs from the current dynamic to adapt new concepts for long-duration mission operations. Today, ground control teams support astronauts with immediate availability to answer questions, resolve issues, and manage activities. In the near future, however, extended communication delays during long-duration missions will require astronauts to become more autonomous. As many of the responsibilities shift from the ground control teams to the astronauts on-board, the concept of operations must also change from how it functions today. With increased astronaut autonomy, software tools must be developed that enable efficient completion of mission tasks without increased mental workload. Designing software tools to facilitate crew autonomy requires development teams to know which data will enhance quick decision making while providing necessary context for situational awareness of systems being managed on-board. NASA's Autonomous Systems and Operations (ASO) team is presently developing a software interface tool, EXPRESS (EXpedite the PRocessing of Experiments for Space Station) 2.5 to enable a long-duration crew to schedule activities for and operate autonomous systems. This paper describes details of the integrated human factors approach that drove the design of the elements of the software tool, including self-managed scheduling, constraint-driven planning, autonomous system fault recovery, and recommended troubleshooting actions. Additionally, this paper will chronicle ASO modifications of the user interface after the team's first flight demonstration, how it was based on lessons learned during software development, as well as from crew feedback in order to develop the current version which will be demonstrated on ISS in 2021. In the upcoming ISS demonstration, the astronaut crew will be given scenarios for scheduling and operating autonomous system activities, including off-nominal scenarios and autonomous system recoveries. The demonstration of the EXPRESS 2.5 tool is a step towards improved levels of autonomy as our new journeys take us farther into space.

autonomy↗

Onboard Autonomy on the Earth Observing One Mission

The Earth Observing One Spacecraft is currently flying The Autonomous Sciencecraft Experiment (ASE) - onboard autonomy software to improve science return. The ASE software enables the spacecraft to autonomously detect and respond to science events occurring on the Earth. ASE includes software systems that perform science data analysis, mission planning, and run-time robust execution. In this article we describe the autonomy flight software and how it enables a new paradigm of autonomous science and mission operations.

autonomy↗