Engineering topics
Publications and source records attributed to Kelley Hashemi.
This is a status report on the m:N working group that has met three times over the last two years. They have identified barriers by domain, detect and avoid use-cases, and further analysis.
This project concerns construction of an orbital and ground resource network that provides Position, Navigation, and Timing (PNT) services for lunar surface operations. While functionally similar to Global Navigation Satellite Systems (GNSS) for Earth, this system will instead build an automated PNT framework utilizing limited infrastructure on board orbiting assets along with a controlled number of highly accurate assets, or anchor nodes. The goal is to use advanced algorithms to autonomously coordinate on demand or as needed asset participation to achieve orbit determination and time synchronization of accuracy sufficient for end-user localization. Other proposed lunar PNT solutions, such as weak signal GPS, will not meet many mission localization requirements without additional user INS augmentation and a dedicated GNSS constellation would require prohibitive infrastructure development. This proposed effort, the Lunar Autonomous Positioning System (LAPS), instead offers a design that could be deployed in the near term and is facilitated by accessible hardware technology.
Traditionally, air traffic management services have been provided by air traffic controllers and managers stationed in ground facilities, employed or contracted by the public sector, and supported by automation. These centralized, human-centric air traffic management services do not scale to accommodate increasing demands from conventional and new entrant operations for access to the national airspace system. One transformation that provides much needed scalability is increasing the level of autonomy of air traffic management by enabling edge agents of the system, including vehicles, operators, and third-party service suppliers, to collectively self-manage independently from the centralized service providers and enabling the automation to also take on more independent traffic management responsibility from the human agents. This paper identifies challenges to increasing the level of autonomy of air traffic management services. It describes a framework to enable a systematic identification of these challenges. The framework consists of a functional breakdown of air traffic management services and several dimensions characterizing different autonomy scales. The autonomy dimensions include the automation level between human and machine agents, the locus of control between centralized and distributed edge agents, cognitive activities for autonomous situation awareness and decision making, intelligence levels ranging from skill-based to expertise-based autonomous behavior, and uncertainty levels of the dynamics and environment in which autonomous agents operate. Several challenges are identified and categorized using the different dimensions of the autonomy framework.
In this paper we introduce a software simulator that has been used to develop an architecture for a low-cost Lunar Autonomous Position, Navigation and Time (PNT) System, LAPS. LAPS is a conceptual architecture for providing autonomous PNT services on and around the Moon using non-dedicated low-cost orbital and ground assets. The simulation tool has been developed to be flexible and is capable of modeling and analyzing the many different capabilities and configurations that the non-dedicated assets could support. The tool models the creation of an ad hoc swarm, the localization of this swarm and the subsequent provision of PNT services from this swarm. We present results from several studies of select configurations chosen to reflect existing and future real-world needs and capabilities.
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The presentation discusses the background and project framing for the m:N body of work in TTT. It also review the m:N technical challenge for Operations of Autonomous Fleets.
Emerging concepts for advanced urban air mobility envision responsive air transportation capabilities that will safely move people and cargo in locations presently underserved by aviation. Expanding aviation services to these locales, particularly for high-density autonomous flight operations over urban centers, will require advances beyond the state-of-the-art techniques for airborne sensing. The emerging field of distributed sensing and ‘smart spaces’ – where sensing, processing, communication, and actuation are embedded in the environment in which agents are acting – may provide attractive alternatives over traditional aviation solutions. This paper outlines the challenges and opportunities for distributed sensing and smart space concepts to meet the emerging needs of advanced urban operations in the national airspace. We present an overview of distributed sensing concepts and research currently being investigated under this endeavor.
As the path towards Urban Air Mobility (UAM) continues to take shape, there are outstanding technical challenges to achieving safe and effective air transportation operations under this new paradigm. To inform and guide technology development for UAM, NASA is investigating the current state-of-the-art in key technology areas including traffic management, detect-and-avoid, and autonomy. In support of this effort, a new perception testbed was developed at NASA Ames Research Center to collect data from an array of sensing systems representative of those that could be found on a future UAM vehicle. This testbed, featuring a Light-Detection-and-Ranging (LIDAR) instrument, a long-wave infrared sensor, and a visible spectrum camera was deployed for a multiday test campaign in the Fog Chamber at Sandia National Laboratories (SNL), in Albuquerque, New Mexico. During the test campaign, fog conditions were created for tests with targets including a human, a resolution chart, and a small unmanned aerial vehicle (sUAV). This paper describes in detail, the developed perception testbed, the experimental setup in the fog chamber, the resulting data, and presents an initial result from analysis of the data with the evaluation of methods to increase contrast through filtering techniques.
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