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Neilan, James H.

Publications and source records attributed to Neilan, James H..

A Mission Concept to Study Multigenerational Mammalian Reproduction in Partial Gravity

A team at NASA Langley Research Center conducted a study during which a conceptual space mission was designed. In this study, rodents are used as human analogs to gather biological and systems data in a relevant environment applicable to future settlements on Mars. The mission concept uniquely addresses the combined effects of long-durations (one-year or greater), autonomous and robotic operations, and biological responses to partial gravity with an emphasis on reproduction. The objectives of this study were to 1) understand challenges associated with designing an artificial gravity habitat that supports the reproduction and maturation of a large animal colony, 2) identify mission architectures and operational concepts to transport and maintain such a facility, and 3) identify fundamental science considerations for mammalian reproduction studies to inform vehicle design. A model demonstration unit was developed to visualize and test certain design concepts that resulted from these considerations. Three versions of this demonstration unit were built over the course of the study, each taking into account lessons learned from the previous version. This paper presents the updated baseline mission and spacecraft design concepts to achieve these objectives, with a specific emphasis on updates since publication in previous works. Analyses of the integrated system trades among the elements which make up the conceptual vehicle are described to address overall feasibility and identify potential integrated design opportunities. The latest iteration of the habitat robotics design and a conceptual design example for autonomous care of crew and systems are also presented. Finally, the conclusion of this conceptual design study, necessary future analyses to enable such a facility, and comments upon other applications of a similar exploration-focused research facilities are addressed.

Rodgers, Erica M.

Using Multimodal Input for Autonomous Decision Making for Unmanned Systems

Autonomous decision making in the presence of uncertainly is a deeply studied problem space particularly in the area of autonomous systems operations for land, air, sea, and space vehicles. Various techniques ranging from single algorithm solutions to complex ensemble classifier systems have been utilized in a research context in solving mission critical flight decisions. Realized systems on actual autonomous hardware, however, is a difficult systems integration problem, constituting a majority of applied robotics development timelines. The ability to reliably and repeatedly classify objects during a vehicles mission execution is vital for the vehicle to mitigate both static and dynamic environmental concerns such that the mission may be completed successfully and have the vehicle operate and return safely. In this paper, the Autonomy Incubator proposes and discusses an ensemble learning and recognition system planned for our autonomous framework, AEON, in selected domains, which fuse decision criteria, using prior experience on both the individual classifier layer and the ensemble layer to mitigate environmental uncertainty during operation.

Neilan, James H.

A Safe Cooperative Framework for Atmospheric Science Missions with Multiple Heterogeneous UAS using Piecewise Bezier Curves

Autonomous operation of UAS holds promise for greater productivity of atmospheric science missions. However, several challenges need to be overcome before such missions can be made autonomous. This paper presents a framework for safe autonomous operations of multiple vehicles, particularly suited for atmospheric science missions. The framework revolves around the use of piecewise Bezier curves for trajectory representation, which in conjunction with path-following and time-coordination algorithms, allows for safe coordinated operations of multiple vehicles.

Mehdi, S. Bilal

Multigenerational Independent Colony for Extraterrestrial Habitation, Autonomy, and Behavior Health (MICEHAB): An Investigation of a Long Duration, Partial Gravity, Autonomous Rodent Colony

The path from Earth to Mars requires exploration missions to be increasingly Earth-independent as the foundation is laid for a sustained human presence in the following decades. NASA pioneering of Mars will expand the boundaries of human exploration, as a sustainable presence on the surface requires humans to successfully reproduce in a partial gravity environment independent from Earth intervention. Before significant investment is made in capabilities leading to such pioneering efforts, the challenges of multigenerational mammalian reproduction in a partial gravity environment need be investigated. The Multi-generational Independent Colony for Extraterrestrial Habitation, Autonomy, and Behavior health is designed to study these challenges. The proposed concept is a conceptual, long duration, autonomous habitat designed to house rodents in a partial gravity environment with the goal of understanding the effects of partial gravity on mammalian reproduction over multiple generations and how to effectively design such a facility to operate autonomously while keeping the rodents healthy in order to achieve multiple generations. All systems are designed to feed forward directly to full-scale human missions to Mars. This paper presents the baseline design concept formulated after considering challenges in the mission and vehicle architectures such as: vehicle automation, automated crew health management/medical care, unique automated waste disposal and hygiene, handling of deceased crew members, reliable long-duration crew support systems, and radiation protection. This concept was selected from an architectural trade space considering the balance between mission science return and robotic and autonomy capabilities. The baseline design is described in detail including: transportation and facility operation constraints, artificial gravity system design, habitat design, and a full-scale mock-up demonstration of autonomous rodent care facilities. The proposed concept has the potential to integrate into existing mission architectures in order to achieve exploration objectives, and to demonstrate and mature common capabilities that enable a range of destinations and missions.

Rodgers, Erica M.

Who's Got the Bridge? - Towards Safe, Robust Autonomous Operations at NASA Langley's Autonomy Incubator

NASA aeronautics research has made decades of contributions to aviation. Both aircraft and air traffic management (ATM) systems in use today contain NASA-developed and NASA sponsored technologies that improve safety and efficiency. Recent innovations in robotics and autonomy for automobiles and unmanned systems point to a future with increased personal mobility and access to transportation, including aviation. Automation and autonomous operations will transform the way we move people and goods. Achieving this mobility will require safe, robust, reliable operations for both the vehicle and the airspace and challenges to this inevitable future are being addressed now in government labs, universities, and industry. These challenges are the focus of NASA Langley Research Center's Autonomy Incubator whose R&D portfolio includes mission planning, trajectory and path planning, object detection and avoidance, object classification, sensor fusion, controls, machine learning, computer vision, human-machine teaming, geo-containment, open architecture design and development, as well as the test and evaluation environment that will be critical to prove system reliability and support certification. Safe autonomous operations will be enabled via onboard sensing and perception systems in both data-rich and data-deprived environments. Applied autonomy will enable safety, efficiency and unprecedented mobility as people and goods take to the skies tomorrow just as we do on the road today.

Allen, B. Danette

Collaborating with Autonomous Agents

With the anticipated increase of small unmanned aircraft systems (sUAS) entering into the National Airspace System, it is highly likely that vehicle operators will be teaming with fleets of small autonomous vehicles. The small vehicles may consist of sUAS, which are 55 pounds or less that typically will y at altitudes 400 feet and below, and small ground vehicles typically operating in buildings or defined small campuses. Typically, the vehicle operators are not concerned with manual control of the vehicle; instead they are concerned with the overall mission. In order for this vision of high-level mission operators working with fleets of vehicles to come to fruition, many human factors related challenges must be investigated and solved. First, the interface between the human operator and the autonomous agent must be at a level that the operator needs and the agents can understand. This paper details the natural language human factors e orts that NASA Langley's Autonomy Incubator is focusing on. In particular these e orts focus on allowing the operator to interact with the system using speech and gestures rather than a mouse and keyboard. With this ability of the system to understand both speech and gestures, operators not familiar with the vehicle dynamics will be able to easily plan, initiate, and change missions using a language familiar to them rather than having to learn and converse in the vehicle's language. This will foster better teaming between the operator and the autonomous agent which will help lower workload, increase situation awareness, and improve performance of the system as a whole.

Trujillo, Anna C.

Towards an Open, Distributed Software Architecture for UxS Operations

To address the growing need to evaluate, test, and certify an ever expanding ecosystem of UxS platforms in preparation of cultural integration, NASA Langley Research Center's Autonomy Incubator (AI) has taken on the challenge of developing a software framework in which UxS platforms developed by third parties can be integrated into a single system which provides evaluation and testing, mission planning and operation, and out-of-the-box autonomy and data fusion capabilities. This software framework, named AEON (Autonomous Entity Operations Network), has two main goals. The first goal is the development of a cross-platform, extensible, onboard software system that provides autonomy at the mission execution and course-planning level, a highly configurable data fusion framework sensitive to the platform's available sensor hardware, and plug-and-play compatibility with a wide array of computer systems, sensors, software, and controls hardware. The second goal is the development of a ground control system that acts as a test-bed for integration of the proposed heterogeneous fleet, and allows for complex mission planning, tracking, and debugging capabilities. The ground control system should also be highly extensible and allow plug-and-play interoperability with third party software systems. In order to achieve these goals, this paper proposes an open, distributed software architecture which utilizes at its core the Data Distribution Service (DDS) standards, established by the Object Management Group (OMG), for inter-process communication and data flow. The design decisions proposed herein leverage the advantages of existing robotics software architectures and the DDS standards to develop software that is scalable, high-performance, fault tolerant, modular, and readily interoperable with external platforms and software.

Cross, Charles D.