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At least 127 records · Page 7

Preliminary Application of Formal Verification to An Autonomy Architecture for Unmanned Aircraft

There is a desire to design autonomous systems in such a way that capabilities can be easily added or re-combined to produce new behaviors while preserving their safety properties. ICAROUS, a prototype software architecture for building safety-centric autonomous unmanned aircraft applications, is designed to support this type of extensibility and re-configurability. In ICAROUS, core capabilities are implemented as individual soft- ware services, so that enabling access to new capabilities simply requires adding new services. To make use of these capabilities, ICAROUS includes a specialized service that provides a general framework for config- uring the relative priorities, conditions, and rules that govern how different modules should be engaged and disengaged during flight. The inherent complexity of coordinating multiple modules under changing conditions makes it difficult to determine whether a particular configuration could have erroneous behaviors in certain circumstances. A robust set of integration tests can help discover errors, but testing can only realistically cover a relatively small proportion of total system behaviors. Developing good tests and interpreting the results to pinpoint the cause of errors when they arise can also be very time-consuming. To supplement testing, formal methods can be used to model and analyze complex systems, achieving better coverage and simplifying the process of finding, understanding, and fixing errors. To demonstrate these benefits, this paper explores the ap- plication of formal methods to ICAROUS. In particular, the Spin model checker is used to specify requirements for and model portions of the system, then verify whether the model satisfies the requirements and find and fix errors when it does not.

Formal Methods↗

A Framework for the Analysis of Deep Neural Networks in Autonomous Aerospace Applications using Bayesian Statistics

Deep Neural Networks (DNNs) are considered to be key components in many autonomous systems. Applications range from vision-based obstacle avoidance to intelligent/learning control and planning. Safety-critical applications as found in the aerospace domain require that the behavior of the DNN is validated and tested rigorously for safety of the autonomous system (AUS). In this paper, we present a framework to support testing of DNNs and the analysis of the network structure. Our framework employs techniques from statistical modeling and active learning to effectively generate test cases for DNN safety testing and performance analysis. We will present results of a case study on a physics-based Deep recurrent residual neural network (DR-RNN), which has been trained to emulate the aerodynamics behavior of a fixed-wing aircraft.

Deep Neural networks↗

Modelling parallel programs and multiprocessor architectures with AXE

AXE, An Experimental Environment for Parallel Systems, was designed to model and simulate for parallel systems at the process level. It provides an integrated environment for specifying computation models, multiprocessor architectures, data collection, and performance visualization. AXE is being used at NASA-Ames for developing resource management strategies, parallel problem formulation, multiprocessor architectures, and operating system issues related to the High Performance Computing and Communications Program. AXE's simple, structured user-interface enables the user to model parallel programs and machines precisely and efficiently. Its quick turn-around time keeps the user interested and productive. AXE models multicomputers. The user may easily modify various architectural parameters including the number of sites, connection topologies, and overhead for operating system activities. Parallel computations in AXE are represented as collections of autonomous computing objects known as players. Their use and behavior is described. Performance data of the multiprocessor model can be observed on a color screen. These include CPU and message routing bottlenecks, and the dynamic status of the software.

Yan, Jerry C.↗

Cooperative Exploration of Rough Martian Terrains with the "Scorpion" Legged Robot as an Adjunct to a Rover.

NASA needs autonomous robotic exploration of difficult (rough and/or steep) scientifically interesting Martian terrains. Concepts involving distributed autonomy for cooperative robotic exploration are key to enabling new scientific objectives in robotic missions. We propose to utilize a legged robot as an adjunct scout to a rover for access to difficult - scientifically interesting - terrains (rocky areas, slopes, cliffs). Our final mission scenario involves the Ames rover platform "K9" and Scorpion acting together to explore a steep cliff, with the Scorpion robot rappelling down using the K9 as an anchor as well as mission planner and executive. Cooperation concepts, including wheeled rappelling robots have been proposed before. Now we propose to test the combined advantages of a wheeled vehicle with a legged scout as well as the advantages of merging of high level planning and execution with biologically inspired, behavior based robotics. We propose to use the 8-legged, multifunctional autonomous robot platform Scorpion that is currently capable of: Walking on different terrains (rocks, sand, grass, ...). Perceiving its environment and modifying its behavioral pattern accordingly. These capabilities would be extended to enable the Scorpion to: communicate and cooperate with a partner robot; climb over rocks, rubble piles, and objects with structural features. This will be done in the context of exploration of rough terrains in the neighborhood of the rover, but inaccessible to it, culminating in the added capability of rappelling down a steep cliff for both vertical and horizontal terrain observation.

Colombano, Silvano P.↗

Supporting Crew Autonomy in Deep Space Exploration: Preliminary Onboard Capability Requirements and Proposed Research Questions. Technical Report of the Autonomous Crew Operations Technical Interchange Meeting

Communication delays are a critical challenge posed by long duration deep space exploration. Space missions historically have relied on an ever-present Mission Control Center (MCC) to direct operations in near real-time. As unanticipated anomalies that defeat fault detection and resolution systems do arise, the lack of real-time communication will significantly weaken what the MCC support represents: a reliable safety net for the flight crew through its deep and diverse areas of expertise and investigative resources. As a consequence, future space vehicles and habitats need to be equipped with capabilities to support the flight crew to operate with little or no ground support. Considerations must be given to vehicle and mission designs that will fortify the traditionally ground-centered safety net and forge new support systems, when communication delays exist. In August 2018, NASA’s Human Research Program, through its Human Factors and Behavioral Performance Element, convened a Technical Interchange Meeting (TIM) on Autonomous Crew Operations at NASA Ames Research Center. The goal of the meeting was to gather input from NASA centers, industry, academia, and branches of the Department of Defense (DoD) to address how intelligent technologies can be applied to augment onboard capabilities to support crew anomaly response. The TIM featured 24 presentations by 29 speakers and hosted a total of 59 attendees, including 43 from 5 NASA centers (Ames, Johnson, Langley, Marshall, and Jet Propulsion Lab) and 4 from the DoD (3 from Army Research Lab and 1 from Naval Postgraduate School), with remaining attendees from academia (e.g., UC Davis, CMU) and industry (e.g., IBM, Siemens). Discussions were centered around three themes: standards and guidelines, lessons learned in analog environments, and technologies. To help provide a framework for discussion, a concept matrix describing anomaly response processes was created prior to the TIM (Figure 1, page 6). The matrix captures the steps involved (monitoring and detection, diagnosis, solution development and evaluation, solution implementation and verification, resolution documentation) as well as the resources and capabilities required to support these steps (data, knowledge, analysis, synthesis, resource management). A wallpaper size printout of the matrix was utilized at the TIM to solicit attendee inputs along the three themes; the activity garnered 108 submissions of ideas. Overall, what emerged from TIM discussions was a picture of mismatch between crew anomaly response needs and support that can be provided by existing intelligent technologies. The needs are broad, spanning multiple steps and processes/resources, with many of which lacking support from existing technologies, such as knowledge management throughout the steps of problem solving (especially in resolution documentation) and manpower management. The solutions provided by existing intelligent technologies are specific to the steps/processes that they are designed to support and constrained to solving only problems similar to those that have occurred before. What is lacking from technologies is typically made up by humans, specifically their complex critical thinking, creative problem solving, and domain expertise. In the end, the TIM highlighted the pressing need to support responses to onboard anomalies during autonomous crew operations, particularly those that have eluded the system tests, inspection, and other assurance processes. Such anomalies can potentially threaten crew and vehicle safety, as well as significantly impact overall operations with additional workload. These fairly rare events are difficult to anticipate and prepare for, given the state-of-the-art in intelligent technologies. This is true even for anomalies that stem from “unknown knowns”—cases in which there is sufficient external information to characterize the problem but the overall pattern fails to be recognized by the problem solver, or in which the internal knowledge needed to solve a problem is held tacitly and potentially accessible by the problem solver but not articulated. It follows that the ability to tackle anomalies lies not only with the availability of relevant information and knowledge but also their accessibility in times of need. To that end, we propose research questions along the following three broad themes: • How intelligent technologies can help make relevant knowledge and information available? • How intelligent technologies can help make relevant knowledge and information accessible? • How intelligent technologies can help support the crew operating as a team in anomaly response processes?

autonomous crew operations↗

Knowledge-based Autonomous Test Engineer (KATE)

Mathematical models of system components have long been used to allow simulators to predict system behavior to various stimuli. Recent efforts to monitor, diagnose, and control real-time systems using component models have experienced similar success. NASA Kennedy is continuing the development of a tool for implementing real-time knowledge-based diagnostic and control systems called KATE (Knowledge based Autonomous Test Engineer). KATE is a model-based reasoning shell designed to provide autonomous control, monitoring, fault detection, and diagnostics for complex engineering systems by applying its reasoning techniques to an exchangeable quantitative model describing the structure and function of the various system components and their systemic behavior.

Parrish, Carrie L.↗

A multitasking behavioral control system for the Robotic All Terrain Lunar Exploration Rover (RATLER)

An alternative methodology for designing an autonomous navigation and control system is discussed. This generalized hybrid system is based on a less sequential and less anthropomorphic approach than that used in the more traditional artificial intelligence (AI) technique. The architecture is designed to allow both synchronous and asynchronous operations between various behavior modules. This is accomplished by intertask communications channels which implement each behavior module and each interconnection node as a stand-alone task. The proposed design architecture allows for construction of hybrid systems which employ both subsumption and traditional AI techniques as well as providing for a teleoperator's interface. Implementation of the architecture is planned for the prototype Robotic All Terrain Lunar Explorer Rover (RATLER) which is described briefly.

Klarer, P.↗

Autonomous mobile robot teams

This paper describes autonomous mobile robot teams performing tasks in unstructured environments. The behavior and the intelligence of the group is distributed, and the system does not include a central command base or leader. The novel concept of the Tropism-Based Cognitive Architecture is introduced, which is used by the robots in order to produce behavior transforming their sensory information to proper action. The results of a number of simulation experiments are presented. These experiments include worlds where the robot teams must locate, decompose, and gather objects, and defend themselves against hostile predators, while navigating around stationary and mobile obstacles.

Agah, Arvin↗

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.↗

Experiments with a small behaviour controlled planetary rover

A series of experiments that were performed on the Rocky 3 robot is described. Rocky 3 is a small autonomous rover capable of navigating through rough outdoor terrain to a predesignated area, searching that area for soft soil, acquiring a soil sample, and depositing the sample in a container at its home base. The robot is programmed according to a reactive behavior control paradigm using the ALFA programming language. This style of programming produces robust autonomous performance while requiring significantly less computational resources than more traditional mobile robot control systems. The code for Rocky 3 runs on an eight bit processor and uses about ten k of memory.

Miller, David P.↗

Capability Considerations for Enhancing Safety on Long Duration Crewed Missions: Insights from a Technical Interchange Meeting on Autonomous Crew Operations

As future flight crews on long duration deep space missions are expected to operate more autonomously, considerations must be given to onboard capabilities and human-computer teaming that will fortify the safety net traditionally provided by the Mission Control Center. In August 2018, the Human Factors and Behavioral Performance Element of NASA's Human Research Program convened a Technical Interchange Meeting (TIM) on Autonomous Crew Operations at NASA Ames Research Center to address how intelligent technologies can be utilized to augment crew capabilities to support real-time anomaly response. In this paper, we highlight three topic areas discussed at the TIM that have direct implications for future crew anomaly response capabilities: smart structures, cognitive assistants, and manpower.

autonomous crew operations↗

Autonomous, Context-Sensitive, Task Management Systems and Decision Support Tools I: Human-Autonomy Teaming Fundamentals and State of the Art

Recent advances in artificial intelligence, machine learning, data mining and extraction, and especially in sensor technology have resulted in the availability of a vast amount of digital data and information and the development of advanced automated reasoners. This creates the opportunity for the development of a robust dynamic task manager and decision support tool that is context sensitive and integrates information from a wide array of on-board and off aircraft sourcesa tool that monitors systems and the overall flight situation, anticipates information needs, prioritizes tasks appropriately, keeps pilots well informed, and is nimble and able to adapt to changing circumstances. This is the first of two companion reports exploring issues associated with autonomous, context-sensitive, task management and decision support tools. In the first report, we explore fundamental issues associated with the development of an integrated, dynamic, flight information and automation management system. We discuss human factors issues pertaining to information automation and review the current state of the art of pilot information management and decision support tools. We also explore how effective human-human team behavior and expectations could be extended to teams involving humans and automation or autonomous systems.

context-sensitive↗

Robotic Precursor Missions for Mars Habitats

Infrastructure support for robotic colonies, manned Mars habitat, and/or robotic exploration of planetary surfaces will need to rely on the field deployment of multiple robust robots. This support includes such tasks as the deployment and servicing of power systems and ISRU generators, construction of beaconed roadways, and the site preparation and deployment of manned habitat modules. The current level of autonomy of planetary rovers such as Sojourner will need to be greatly enhanced for these types of operations. In addition, single robotic platforms will not be capable of complicated construction scenarios. Precursor robotic missions to Mars that involve teams of multiple cooperating robots to accomplish some of these tasks is a cost effective solution to the possible long timeline necessary for the deployment of a manned habitat. Ongoing work at JPL under the Mars Outpost Program in the area of robot colonies is investigating many of the technology developments necessary for such an ambitious undertaking. Some of the issues that are being addressed include behavior-based control systems for multiple cooperating robots (CAMPOUT), development of autonomous robotic systems for the rescue/repair of trapped or disabled robots, and the design and development of robotic platforms for construction tasks such as material transport and surface clearing.

Huntsberger, Terry↗

Robonaut Mobile Autonomy: Initial Experiments

A mobile version of the NASA/DARPA Robonaut humanoid recently completed initial autonomy trials working directly with humans in cluttered environments. This compact robot combines the upper body of the Robonaut system with a Segway Robotic Mobility Platform yielding a dexterous, maneuverable humanoid ideal for interacting with human co-workers in a range of environments. This system uses stereovision to locate human teammates and tools and a navigation system that uses laser range and vision data to follow humans while avoiding obstacles. Tactile sensors provide information to grasping algorithms for efficient tool exchanges. The autonomous architecture utilizes these pre-programmed skills to form complex behaviors. The initial behavior demonstrates a robust capability to assist a human by acquiring a tool from a remotely located individual and then following the human in a cluttered environment with the tool for future use.

Diftler, M. A.↗

Mapping a Path to Autonomous Flight in the National Airspace

The introduction of autonomous flight, whether military, commercial, or civilian, into the National Airspace System (NAS) will present significant challenges. Minimizing the impact and preventing the changes from becoming disruptive, rather than an enhancing technology will not be without difficulty. From obstacle detection and avoidance to real-time verification and validation of system behavior, there are significant problems which must be solved prior to the general acceptance of autonomous systems. This paper examines some of the key challenges and the multi-disciplinary collaboration which must occur for autonomous systems to be accepted as equal partners in the NAS.

Lodding, Kenneth N.↗

Distributed Spacecraft Autonomy - Development of Swarm Autonomy Capability and Scalability for Spacecraft

The Distributed Spacecraft Autonomy project is developing a suite of software tools that enable an operator to command and receive data from a swarm as a single entity, enable a swarm to autonomously coordinate its actions via distributed decision making and reactive closed-loop control, and model swarm behavior in the presence of anomalies or failures. Our use case is the mapping of the electron density of the ionosphere using radio tomography by coordinating the selection of appropriate GPS channels, and by recording Total Electron Count (TEC) measurements. DSA will be demonstrated onboard the NASA Ames Starling mission – a swarm of four small, LEO spacecraft, scheduled to launch in 2021. We will also perform a ground demonstration with simulated and hardware-in-the-loop elements, to validate the tools for controlling swarms of up to 100 assets. The capability to communicate autonomously between the swarm satellites is demonstrated via a sophisticated simulation architecture. Historical Plasmasphere TEC data obtained via dual-band Novatel GPS Receivers are utilized as a representative input dataset for the swarm. The representative TEC data and GPS satellite observability information is fed to the autonomous software package in place of a true real-time ground data collection process. The swarm satellites actively share status updates amongst one another and utilize multi-agent decision making to optimally identify regions of interest in the TEC distribution. The software, aware of the bandwidth limitations of the swarm satellites, prioritizes explorative measurements, which define the range of observability for the satellites, as well as exploitative measurements, which focus on maximizing the observance potential of regions with prolonged, elevated TEC density. The science of this study can ultimately be used to determine the dynamics and coupling of Earth’s magnetosphere, ionosphere, and atmosphere and their response to solar and terrestrial inputs. The findings can be applied to the imaging of critical, transient phenomena in the magnetosphere in later missions. Meanwhile, the swarm autonomy capabilities have far reaching potential in future satellite missions. As an experimental demonstration of the autonomous capabilities of the network, a message is first printed within a core Flight Executive (cFE) application. Two cFE applications that communicate with one another within the same core Flight System (cFS) are shown. Communication between mission applications on the internal cFE bus is extended to utilize Data Distribution Service (DDS) for vehicle-to-vehicle networking. The DDS middleware provides reliable delivery, routing, and topic subscription features over User Datagram Protocol (UDP). Leveraging Linux containerization, a networked set of satellite instances are generated by script to simulate swarm behavior. Swarm commanding and synchronization through the network is demonstrated under various topologies and data-loss conditions. Finally, autonomous swarm scalability from 2 satellites to 100 satellites is shown.

Distributed Autonomy↗

Distributed Spacecraft Autonomy (DSA): Development of Swarm Autonomy Capability and Scalability for Spacecraft

The Distributed Spacecraft Autonomy project is developing a suite of software tools that enable an operator to command and receive data from a swarm as a single entity, enable a swarm to autonomously coordinate its actions via distributed decision making and reactive closed-loop control, and model swarm behavior in the presence of anomalies or failures. Our use case is the mapping of the electron density of the ionosphere using radio tomography by coordinating the selection of appropriate GPS channels, and by recording Total Electron Count (TEC)measurements. DSA will be demonstrated on board the NASA Ames Starling mission a swarm of four small, LEO spacecraft, scheduled to launch in 2021. We will also perform a ground demonstration with simulated and hardware-in-the-loop elements, to validate the tools for controlling swarms of up to 100 assets.The capability to communicate autonomously between the swarm satellites is demonstrated via a sophisticated simulation architecture. Historical Plasma sphere TEC data obtained via dual-band Novatel GPS Receivers are utilized as a representative input data set for the swarm. The representative TEC data and GPS satellite observability information is fed to the autonomous software package in place of a true real-time ground data collection process. The swarm satellites actively share status updates amongst one another and utilize multi-agent decision making to optimally identify regions of interest in the TEC distribution. The software,aware of the bandwidth limitations of the swarm satellites, prioritizes explorative measurements,which define the range of observability for the satellites, as well as exploitative measurements,which focus on maximizing the observance potential of regions with prolonged, elevated TEC density. The science of this study can ultimately be used to determine the dynamics and coupling of Earth's magnetosphere, ionosphere, and atmosphere and their response to solar and terrestrial inputs. The findings can be applied to the imaging of critical, transient phenomena in the magnetosphere in later missions. Meanwhile, the swarm autonomy capabilities have far reaching potential in future satellite missions.As an experimental demonstration of the autonomous capabilities of the network, a message is first printed within a core Flight Executive (cFE) application. Two cFE applications that communicate with one another within the same core Flight System (cFS) are shown.Communication between mission applications on the internal cFE bus is extended to utilize Data Distribution Service (DDS) for vehicle-to-vehicle networking. The DDS middle ware provides reliable delivery, routing, and topic subscription features over User Data gram Protocol (UDP).Leveraging Linux containerization, a networked set of satellite instances are generated by script to simulate swarm behavior. Swarm commanding and synchronization through the network is demonstrated under various topologies and data-loss conditions. Finally, autonomous swarms calability from 2 satellites to 100 satellites is shown.

Fugate, Jason↗

Autonomous and Autonomic Systems: A Paradigm for Future Space Exploration Missions

NASA increasingly will rely on autonomous systems concepts, not only in the mission control centers on the ground, but also on spacecraft and on rovers and other assets on extraterrestrial bodies. Automomy enables not only reduced operations costs, But also adaptable goal-driven functionality of mission systems. Space missions lacking autonomy will be unable to achieve the full range of advanced mission objectives, given that human control under dynamic environmental conditions will not be feasible due, in part, to the unavoidably high signal propagation latency and constrained data rates of mission communications links. While autonomy cost-effectively supports accomplishment of mission goals, autonomicity supports survivability of remote mission assets, especially when human tending is not feasible. Autonomic system properties (which ensure self-configuring, self-optimizing self-healing, and self-protecting behavior) conceptually may enable space missions of a higher order into any previously flown. Analysis of two NASA agent-based systems previously prototyped, and of a proposed future mission involving numerous cooperating spacecraft, illustrates how autonomous and autonomic system concepts may be brought to bear on future space missions.

Truszkowski, Walter F.↗