Embodiments are disclosed for a vehicle control system and related sub-components that together provide an operator with a plurality of specific modes of operation, wherein various modes of operation incorporate different levels of autonomous control. Through a control user interface, an operator can move between certain modes of control even after vehicle deployment. Specialized autopilot system components and methods are employed to ensure smooth transitions between control modes. Empowered by the multi-modal control system, an operator can even manage multiple vehicles simultaneously.

Vehicle control system including related methods and components

Programming complex embedded systems involves reasoning through intricate system interactions along lengthy paths between sensors, actuators, and control processors. This is a challenging, time-consuming, and error-prone process requiring significant interaction between engineers and software programmers. Furthermore, the resulting code generally lacks modularity and robustness in the presence of failure. Model-based programming addresses these limitations, allowing engineers to program reactive systems by specifying high-level control strategies and by assembling commonsense models of the system hardware and software. In executing a control strategy, model-based executives reason about the models "on the fly," to track system state, diagnose faults, and perform reconfigurations. This paper develops the reactive model-based programming language (RMPL) and its executive, called Titan. RMPL provides the features of synchronous, reactive languages, with the added ability of reading and writing to state variables that are hidden within the physical plant being controlled. Titan executes an RMPL program using extensive component-based declarative models of the plant to track states, analyze anomalous situations, and generate novel control sequences. Within its reactive control loop, Titan employs propositional inference to deduce the system's current and desired states, and it employs model-based reactive planning to move the plant from the current to the desired state.

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Model-based programming of intelligent embedded systems and robotic space explorers

*In 2007 the NASA Office of Chief Engineer commissioned a multi-center study to bring forth technical and managerial strategies to address risks from growth in size and complexity of flight software in NASA’s space missions. The motivation for the study grew from problems attributed to flight software in a variety of missions—in both pre-launch and post-launch activities—and concerns that such problems were growing with the expanding role of flight software. The study was tasked to examine the growth in flight software size and complexity, recommend ways to reduce and better manage complexity, and identify methods of testing complex logic. This report examines complexity throughout the engineering lifecycle—from requirements definition through design, development, verification, and operations—and presents sixteen findings and associated recommendations.

NASA Study on Flight Software Complexity

A disk drive is disclosed including a disk having a plurality of servo tracks. The servo tracks are banded together to form a plurality of servo track bands, and each servo sector comprises a fine track address that identifies one of the servo tracks. The disk drive further comprises a head attached to a distal end of an actuator arm operable to generate a read signal by reading the disk, and a mechanical position sensor operable to detect a coarse position of the actuator arm. The coarse position is processed to identify one of the servo track bands, and the read signal is processed to detect one of the fine track addresses, wherein the detected fine track address identifies a servo track within the identified servo track band. The identified servo track band is combined with the detected fine track address to generate a servo track address.

Disk drive employing coarse position feedback from mechanical position sensor to improve format efficiency

A computer system implementing a fault detection and isolation technique that tracks failed physical devices by identification (ID) codes embedded in each component of the computer for which the ability to detect faults and isolate failed devices is disclosed. The computer system comprises one or more CPU's, one or more memory modules, a master control device, such as an I2C master, and a North bridge logic device coupling together the CPU's, memory modules, and master control device. The master control device also connects to the CPU's and memory modules over a serial bus, such as an I2C bus. Each CPU and memory module includes an ID code that uniquely identifies and distinguishes that device from all other devices in the computer system. The computer also includes a non-volatile memory device coupled to the CPU for storing a failed device log which includes a list of ID codes corresponding to failed physical devices. After a device is determined to be non-functional, one of the CPU's stores that device's unique ID code in the failed device log. Using the list of physical devices from the failed device log, the CPU creates a logical resource map which includes a list of logical addresses of all available (i.e., fully functional) devices. The logical resource map is provided to the computer's operating system which isolates failed devices by only permitting access to those logical devices listed as available in the logical resource map.

Computer system implementing fault detection and isolation using unique identification codes stored in non-volatile memory

An autonomous control system supports autonomous operation of the a spacecraft in carrying out mission objective commands. The control system also provides autonomous fault detection, isolation and recovery. Performance problems and anomalies are detected and accounted for in the carrying out mission objectives. A mission manager module analyzes all incoming mission objective commands to verify that sufficient system resources are available and not already dedicated to other pending mission objective commands. A command processor is included to translate acceptable mission objective commands into lower level command sequences for delivery to a flight manager controlling the underlying spacecraft systems. The mission manager reanalyzes all pending mission objective commands whenever unexpected performance or fault conditions are detected. The mission objective commands can be constructed in a hierarchical fashion, with many sequences predefined within the spacecraft. All portions of the autonomous control system, including software and associated data, can be readily replaced, supplemented or disabled at any time before, during or after launch.

Method and system for autonomous spacecraft control

Achieving consistently high levels of productivity for surface exploration missions has been a challenge for Mars missions. While the rovers have made major discoveries and accomplished a large number of objectives, they often require a great deal of effort from the operations teams and achievingobjectives can take longer than anticipated. This paper describes the early stages of a multi-year project to investigate solutions for enhancing surface mission productivity. A primary focus of this early stage is to conduct in-depth studies of Mars Science Laboratory science campaigns to gain a deeper understanding of the factors that impact productivity, and to use this understanding to identify potential changes to flight software and ground operations practices to increase productivity. We present the science campaigns we have selected along with a conceptual model of how surface missions achieve objectives that is used to guide the study. We also provide some early thoughts on the technologies, and their interactions, which we believe will play an important role in addressing surface mission productivity challenges.We are in the early stages of a multi-year project to studyand address productivity challenges of future surface missions. We have identified campaigns from the MSL missionfor study which we believe will yield valuable informationabout the nature of surface mission productivity challenges.Based on preliminary analysis from the data collected weanticipate that the lessons from these case studies will helpdevelop and mature our concepts for changes to flight andground systems to address these challenges.While the focus of our work is on Mars rover missions, webelieve the concepts in the work will be applicable to a variety of in-situ explorers, including Venus, and Titan, as wellas orbital missions, such as the Europa orbiter. These missions will also benefit from the ability to adapt and respondto the latest state of the spacecraft and its environment.

Productivity challenges for Mars rover operations

A fault identification, isolation and fault recovery system autonomously controls spacecraft operational systems. A fault detection and isolation module monitors the operational systems, identifies faults via such monitoring and attempts to isolate component causing the fault. Isolation may constitute a plurality of hierarchically arranged techniques that enhance speed and maximize the likelihood of identifying a correct hypothesis regarding the actual failure. The fault isolation and fault recovery modules are bounded by a severe fault override module which places the spacecraft operational systems in a safe mode or state. Thus, the override module ensures rapid entry into the safe mode while preventing an erroneous hypothesis serviced by the fault recovery module from driving the system beyond acceptable limits. A high level command processor receives command sequences from remote ground support stations and from the on-board fault recovery module. A ground based test bed attached to a ground support systems is used to generate verified high level fault recovery scripts before and during a mission to bolster fault recovery capabilities.

In situ method and system for autonomous fault detection, isolation and recovery

Arcsecond Space Telescope Enabling Research In Astrophysics (ASTERIA) is a 6U CubeSat space telescope (10 cm × 20 cm × 30 cm, 10 kg). ASTERIA's primary mission objective was demonstrating two key technologies for reducing systematic noise in photometric observations: high-precision pointing control and high-stability thermal control. ASTERIA demonstrated 0farcs5 rms pointing stability and ±10 mK thermal control of its camera payload during its primary mission, a significant improvement in pointing and thermal performance compared to other spacecraft in ASTERIA's size and mass class. ASTERIA launched in 2017 August and deployed from the International Space Station in 2017 November. During the prime mission (2017 November–2018 February) and the first extended mission that followed (2018 March–2018 May), ASTERIA conducted opportunistic science observations, which included the collection of photometric data on 55 Cancri, a nearby exoplanetary system with a super-Earth transiting planet. The 55 Cancri data were reduced using a custom pipeline to correct complementary metal-oxide semiconductor (CMOS) detector column-dependent gain variations. A Markov Chain Monte Carlo approach was used to simultaneously detrend the photometry using a simple baseline model and fit a transit model. ASTERIA made a marginal detection of the known transiting exoplanet 55 Cancri e (~2 ${R}_{\oplus }$), measuring a transit depth of 374 ± 170 ppm. This is the first detection of an exoplanet transit by a CubeSat. The successful detection of super-Earth 55 Cancri e demonstrates that small, inexpensive spacecraft can deliver high-precision photometric measurements.

https://iopscience.iop.org/article/10.3847/1538-3881/ab8bcc/pdf

Demonstrating High-precision Photometry with a CubeSat: ASTERIA Observations of 55 Cancri e

This paper presents a model-based fault management (FM) system designed to provide off-nominal state detection and isolation capabilities that are key components to assessing spacecraft state awareness. The ability to autonomously isolate spacecraft failures to component levels will enable faster and more targeted responses and recovery thereby reducing down time. The use of model-based systems and practices is being explored by the FM community as a viable approach to developing more capable, autonomous systems in order to meet mission objectives. Model-based systems can provide better fault identification than traditional methods of fault detection such as limit-checking. They also lend themselves to more straight-forward approaches to verification and validation. We have chosen a particular model-based technique called Constraint Suspension for autonomous fault detection and isolation that does not require explicit fault modeling. The system is composed of a diagnostic engine and nominal system models of the target application, for example sensors and actuators. Sensed data are propagated through models of nominal system behavior. Faults are diagnosed when inconsistencies arise between sensed and modeled data. Several benefits result from this choice. First, because knowledge of faulty behavior is not required, it is possible to detect unanticipated and unforeseen faults. In fact, anomalous, degraded, and failed states all can be detected. Second, the same models used for nominal analyses and operations can be re-used for fault management, saving development resources and time. Third, the core diagnostic engine algorithm is complete and requires no additions to accommodate a potentially growing number of faults over time resulting in a relatively compact software footprint. Related to the second and third points is that the core algorithm and, potentially, models can be reused from mission to mission. Finally, the system can be used early in the design phase as a tool for sensor placement analyses and model verification. Health information produced by the FM system can be used to make resource allocation and planning and scheduling decisions by ground operations or by other on-board autonomy agents. Autonomous fault detection, isolation, and recovery (FDIR) on board space vehicles will provide protection and increased mission availability and reliability. On the ground such systems enable lights-out monitoring as well as training and support for operators. This paper presents the development of fault detection and isolation algorithms and models. Application of the system to a spacecraft attitude control system is discussed. Finally we apply Model-Based Systems Engineering (MBSE) modeling patterns to the fault management system models as a way to facilitate the development of the models through the use of SysML.

Lorraine Fesq

Papers

Method and system for autonomous spacecraft control

Productivity challenges for Mars rover operations

In situ method and system for autonomous fault detection, isolation and recovery

Demonstrating High-precision Photometry with a CubeSat: ASTERIA Observations of 55 Cancri e

Model-based off-nominal state isolation and detection system for autonomous fault management