Progress and Future Development toward a UAT ADS-B Transmitter for Space Operations

Continuing Education Free Session #5 - 1 FBPE CE Hour Background ADS-B Overview MITRE UBR-TX UBR-ERAU ADS-B Payload Requirements Design and Implementation System Qualification Ground tests Near Space Corporation’s Nano Balloon System Terminal Velocity Aerospace’s RED-4U prototype spacecraft Path Forward Conclusio

Integrating Unmanned Aircraft Systems into the National Airspace System

Continuing Education Free Session #4 - 1 FBPE CE Hour Industry Overview Systems Overview FAR Part 107 Recent News UAS Applications UAS Research toward Integration Question

A Technology Survey of Emergency Recovery and Flight Termination Systems for UAS

For safe flight in the National Airspace System (NAS), either under the current interim rules or under anticipated longer-term regulatory guidelines facilitating unmanned aircraft system (UAS) access to the NAS, the UAS must incorporate technologies and flight procedures to ensure that neither people nor property in the air, on the ground, or on or in the water are endangered by the failure of an onboard component, by inappropriate unmanned aircraft (UA) response to pilot commands, or by inadvertent entry by the UA into prohibited airspace. The aircraft must be equipped with emergency recovery (ER) procedures and technologies that ensure that in the event of such a failure that the UA is recovered intact with minimal risk to other aircraft, people, or property. Finally, should ER procedures prove ineffective and it is impossible to recover the UA, the pilot-in-command and/or the UAS may engage flight termination (FT) procedures-activities to ensure that the UA is safely destroyed (should the UA be so equipped) or immediately grounded. Together ER and FT are referred to as emergency recovery and flight termination (ERFT). This paper presents a technology survey of ERFT technologies and procedures as applied toward unmanned aircraft

Examination of Urban Air Mobility Integration into the National Airspace System

The Advanced Air Mobility (AAM) initiative aims to enhance air transportation for people and cargo in areas with limited aviation services. The Urban Air Mobility (UAM) concept, under AAM, focuses on improving transportation connectivity within metropolitan areas. The FAA’s ASSURE UAS Center of Excellence has sponsored a project to provide recommendations for future technological developments, UAM airspace integration, infrastructure enhancements, and new regulations to support UAM flights. The team’s first milestone was a literature review to identify past work relevant to UAM, including airspace and operational constraints, infrastructure requirements, and communication, navigation, and surveillance (CNS) requirements. Two dominant concepts of operations were identified, one by the FAA and one by NASA. The team’s second milestone was to examine a UAM corridor concept in Daytona Beach Class C airspace to determine the impact of UAM operations on ATC. The FAA advocates the use of helicopter routes for a measured approach to NAS integration. Since Daytona Class C lacks published helicopter routes, the team developed UAM corridors with input from various airspace users. Key findings suggest a crawl, walk, run development of UAM into Class C airspace is needed, with airspace concepts and system complexities evolving as new UAM features are developed and integrated to meet each UAM Maturity Level

Psychosocial Risk Factors in Disordered Gambling: A Descriptive Systematic Overview of Vulnerable Populations

Background: Gambling is a behaviour engaged in by millions of people worldwide; for some, gambling can become a severely maladaptive behaviour, and previous research has identified a wide range of psychosocial risk factors that can be considered important for the development and maintenance of disordered gambling. Although risk factors have been identified, the homogeneity of risk factors across specific groups thought to be vulnerable to disordered gambling is to date, unexplored. Methods: To address this, the current review sought to conduct a systematic overview of literature relating to seven vulnerable groups: young people and adolescents, older adults, women, veterans, indigenous peoples, prisoners, and low socio-economic/income groups. Results: Multiple risk factors associated with disordered gambling were identified; some appeared consistently across most groups, including being male, co-morbid mental and physical health conditions, substance use disorders, accessibility and availability of gambling, form and mode of gambling, and experience of trauma. Further risk factors were identified that were specific to each vulnerable group. Conclusion: Within the general population, certain groups are more vulnerable to disordered gambling. Although some risk factors are consistent across groups, some risk factors appear to be group specific. It is clear that there is no homogenous pathway in to disordered gambling, and that social, developmental, environmental and demographic characteristics can all interact to influence an individual’s relationship with gambling

Richard Stansbury

Dr. Richard S. Stansbury is an associate professor of computer engineering and computer science at Embry-Riddle Aeronautical University in Daytona Beach, FL. He has supported FAA’s Office of Commercial Space Transportation in the development of an ADS-B prototype for reusable suborbital launch vehicles, and is the ERAU representative for the FAA Center of Excellence for Commercial Space Operations. Additionally, he is actively involved in unmanned aircraft system (UAS) research and is the university PI for the ASSURE FAA Center of Excellence for Unmanned Aircraft Systems. He teaches capstone senior design for his department and is the program coordinator for the Master of Science in Unmanned and Autonomous Systems Engineering.https://commons.erau.edu/stm-images/1048/thumbnail.jp

T4-D: Development and Delivery of a Multidisciplinary Online Course on Unmanned Aircraft Design

The design of unmanned aircraft systems is a multidisciplinary activity across a variety of subsystems both onboard the unmanned aircraft and its ground-based infrastructure. Within the UAS domain, the airworthiness of the designed system must be addressed through across the engineering and product lifecycles. This paper discusses a new course at Embry-Riddle Aeronautical University (ERAU), UAS 501: Introduction to Unmanned Aircraft Design. The course was delivered to ERAU students as part of the Master of Science in Unmanned and Autonomous Systems Engineering program and to a cohortbased ERAU Certificate of Study in Airworthiness Engineering program in partnership with Northrop Grumman Corporation. The paper will address the curriculum, its delivery, and the insights gained in educating a mixed-cohort of traditional and non-traditional students from a variety of engineering academic and professional backgrounds through both synchronous and asynchronous distance deliver

Dr. Richard Stansbury

Richard S. Stansbury is an Associate Professor of Computer Science and Computer Engineering at Embry-Riddle Aeronautical University, Daytona Beach. He is the university\u27s research lead for the ASSURE FAA Center of Excellence for Unmanned Aircraft Systems (UAS). He received his BS and MS degrees in Computer Engineering (2002 and 2004 respectively) and a PhD in Computer Science (2007) from the University of Kansas. As a graduate research assistant, he developed autonomous ground vehicles for operation in Greenland and Antarctica.https://commons.erau.edu/space-congress-bios-2018/1017/thumbnail.jp

Constraint-based task selection and configuration for autonomous mobile robots

Dissertation (Ph.D.)--University of Kansas, Electrical Engineering & Computer Science, 2007.An autonomous mobile robot must be capable of rationally selecting its tasks in order to achieve some state or goal. Rule-based systems encode system knowledge into a set of rules that guide the robot. The dynamic nature of the world is seldom consistent enough to support the rigidity of rules. A new decision maker is needed that expresses the problem as intuitively as rule-based systems with flexibility, extensibility and generalizability. The constraint-based methods can be used to model the problem of selecting and configuring tasks for mobile robots. Constraint Satisfaction Problems (CSPs) provides a framework in which multiple conflicting constraints upon the robot can be resolved in such a way that the robot not only performs correctly, but also meets or exceeds its performance requirements. Constraints also provide the intuitive means of specifying the decision model without the rigidity of rules. Performance objectives are incorporated into the constraint model so that the decision-making system is capable of rationally guiding the robot through actions that best meet its current needs and goals. In this dissertation, a framework and decision maker for robot task selection and configuration is developed. Tasks under this framework are modeled as constraint satisfaction problems. A common software interface was used in order to support the uniform composition of the CSP models. The solution to the CSP provides the selection of a task and its configuration. A utility function is used to select a single solution, if multiple solutions are generated. The framework is demonstrated for three unique robot scenarios: a delivery robot, a polar robot, and an urban search and rescue robot. The delivery robot scenario models tasks for a mobile robot responsible for delivery of items within an office environment. It provides an initial proof-of-concept. Constraint models are constructed for a charge task, a pickup item task, and a deliver item task. The solution to the CSP configures the task execution by specifying the satisfying speed and path for the robot to follow. The performance of the system given the task load, which is directly proportional to the size of the CSP model, is evaluated. Results show a significant increase in computation time when the number of simultaneous delivery requests grow beyond five tasks; however, the delivery failure rate remained lower than a traditional rule-based approach as the load increased. The polar robot scenario models a autonomous mobile robot for remote sensing of Polar Regions The simulation of the polar robot includes a number of remote sensing instruments, including a synthetic aperture radar (SAR), accumulation radar, gravimeter, magnetometer, and IR spectrometer. The robot is also equipped with a solar and a wind generator. The challenge was to balance robot survival and data collection over a full Antarctic year. Constraint models for each instrument, generator, and task are implemented and evaluated versus a rule-based system. The constraint-based system produced significantly lower failure rates, 70% or lower, versus a near 100% failure rate for the rule-based system. The mean survival time using the constraint-based decision maker is greater than 250 days; and the rule-based systems mean survival is less than 200 days. The mean mission completeness of the constraint-based system is significantly greater than the rule-based system, at a 95% confidence level, for four out of five experimental configurations of the polar scenario. The urban search and rescue scenario (USAR) models a mobile robot for the mapping and exploration of collapsed buildings to locate victims and hazards. The robot and its environment are simulated based on works on robot-assisted search and rescue. Task models are constructed for searching, reporting results to the rescue party, obtaining repairs, and charging. Eight unique experiment configurations are developed with varying victim injury levels, number of blocked locations, and topologies (hospital and hotel). The constraint-based system performed statistically better than the rule-based system for two out of eight configurations for mean victims rescued; two out of eight for hazards localized; four out of eight for mean number of collisions; and four out of eight for locations mapped. The constraint-based framework meets or exceeds the performance of the rule-based system. The new decision framework is capable of guiding a variety of mobile robots through rational decisions for task selection and configuration. This is demonstrated in this dissertation for three different scenarios. The framework is flexible to changes in the environment, mission, or tasks. It is also extensible as constraint models can be extended to develop models for new tasks. This work demonstrates that constraint-based decision making is a viable apporach to robot task selection and configuration, and performs better than rule-based systems over a variety of applications