Challenges in autonomy

[Subtitle:] The Quest for Full Autonomy in Unmanned Flight and the Integration of Unmanned Systems into the NA

Dependable and Certifiable Real-World Systems – Issue of Software Engineering Education

Embedded software and dedicated hardware are vital elements of the modern world, from personal electronics to transportation, from communication to aerospace, from military to gaming, from medical systems to banking. Combinations of even minor hardware or software defects in a complex system may lead to violation of safety with or even without evident system failure, a major problem that the computing profession faces is the lack of a universal approach to unite the dissimilar viewpoints presented by computer science, with its discrete and mathematical underpinnings, and by computer engineering, which focuses on building real systems and considering spatial and material constraints of space, energy, and time. Modern embedded systems include both viewpoints: microprocessors running software and programmable electronic hardware created with an extensive use of software. The gap between science and engineering approaches is clearly visible in engineering education. This survey paper focuses on exploring the commonalities between building software and building hardware in an attempt to establish a new framework for rejuvenating computing education, specifically software engineering for dependable systems. We present here a perspective on software/hardware relationship, aviation system certification, role of software engineering education, and future directions in computing

Cooperative and non-cooperative sense-and-avoid in the CNS+A context: a unified methodology

A unified approach to cooperative and noncooperative Sense-and-Avoid (SAA) is presented that addresses the technical and regulatory challenges of Unmanned Aircraft Systems (UAS) integration into nonsegregated airspace. In this paper, state-of-the-art sensor/system technologies for cooperative and noncooperative SAA are reviewed and a reference system architecture is presented. Automated selection of sensors/systems including passive and active Forward Looking Sensors (FLS), Traffic Collision Avoidance System (TCAS) and Automatic Dependent Surveillance - Broadcast (ADS-B) system is performed based on Boolean Decision Logics (BDL) to support trusted autonomous operations during all flight phases. The BDL adoption allows for a dynamic reconfiguration of the SAA architecture, based on the current error estimates of navigation and tracking sensors/systems. The significance of this approach is discussed in the Communication, Navigation and Surveillance/Air Traffic Management and Avionics (CNS+A) context, with a focus on avionics and ATM certification requirements. Additionally, the mathematical models employed in the SAA Unified Method (SUM) to compute the overall uncertainty volume in the airspace surrounding an intruder/obstacle are described. In the presented methodology, navigation and tracking errors affecting the host UAS platform and intruder sensor measurements are translated to unified range and bearing uncertainty descriptors. Simulation case studies are presented to evaluate the performance of the unified approach on a representative UAS host platform and a number of intruder platforms. The results confirm the validity of the proposed unified methodology providing a pathway for certification of SAA systems that typically employ a suite of non-cooperative sensors and/or cooperative systems

Intelligent Systems for Unmanned Aircraft Safety Certification

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/97143/1/AIAA2012-958.pd

R2U2: Tool Overview

R2U2 (Realizable, Responsive, Unobtrusive Unit) is an extensible framework for runtime System HealthManagement (SHM) of cyber-physical systems. R2U2 can be run in hardware (e.g., FPGAs), or software; can monitorhardware, software, or a combination of the two; and can analyze a range of different types of system requirementsduring runtime. An R2U2 requirement is specified utilizing a hierarchical combination of building blocks: temporal formula runtime observers (in LTL or MTL), Bayesian networks, sensor filters, and Boolean testers. Importantly, the framework is extensible; it is designed to enable definitions of new building blocks in combination with the core structure. Originally deployed on Unmanned Aerial Systems (UAS), R2U2 is designed to run on a wide range of embedded platforms, from autonomous systems like rovers, satellites, and robots, to human-assistive ground systems and cockpits. R2U2 is named after the requirements it satisfies; while the exact requirements vary by platform and mission, the ability to formally reason about realizability, responsiveness, and unobtrusiveness is necessary for flight certifiability, safety-critical system assurance, and achievement of technology readiness levels for target systems. Realizability ensures that R2U2 is suficiently expressive to encapsulate meaningful runtime requirements while maintaining adaptability to run on different platforms, transition between different mission stages, and update quickly between missions. Responsiveness entails continuously monitoring the system under test, real-time reasoning, reporting intermediate status, and as-early-as-possible requirements evaluations. Unobtrusiveness ensures compliance with the crucial properties of the target architecture: functionality, certifiability, timing, tolerances, cost, or other constraints

Delivery Drones - Just a Hype? Towards Autonomous Air Mobility Services at Scale

While hype often arises around emerging technologies, delivery drones have received a significant share of attention in recent years. A variety of applications for drone networks formed, from delivering medical goods to drone-delivered pizza. Nevertheless, high expectations did not yet result in a widespread deployment of drones to improve logistic networks. We conducted semi-structured interviews with drone and aviation experts to derive a taxonomy of challenges for autonomous drone operations and gain practical insight into promising solution approaches that could transform the current hype into sound business models. Our findings comprise a multitude of operational, technical, social and legal issues that have not been identified in literature. Societal adaption and the development and interaction with AI-based systems pose a major challenge to provide autonomous air mobility services in the near future

The Effect of Pilot and Air Traffic Control Experiences & Automation Management Strategies on UAS Mission Task Performance

Unmanned aircraft are relied on now more than ever to save lives and support the troops in the recent Operation Enduring Freedom and Operation Iraqi Freedom. The demands for UAS capabilities are rapidly increasing in the civilian sector. However, UAS operations will not be carried out in the NAS until safety concerns are alleviated. Among these concerns is determining the appropriate level of automation in conjunction with a suitable pilot who exhibits the necessary knowledge, skills, and abilities to safely operate these systems. This research examined two levels of automation: Management by Consent (MBC) and Management by Exception (MBE). User experiences were also analyzed in conjunction with both levels of automation while operating an unmanned aircraft simulator. The user experiences encompass three individual groups: Pilots, ATC, and Human Factors. Performance, workload, and situation awareness data were examined, but did not show any significant differences among the groups. Shortfalls and constraints are heavily examined to help pave the wave for future research

Model-based System Health Management and Contingency Planning for Autonomous UAS

Safe autonomous operations of an Unmanned Aerial System (UAS) requires that the UAS can react to unforeseen circumstances, for example, after a failure has occurred. In this paper we describe a model-based run-time architecture for autonomous on-board diagnosis, system health management, and contingency management. This architecture is being instantiated on top of NASA's Core Flight System (cFS/cFE) as amajor component of the on-board AutonomousOperating System (AOS). We will describe our diagnosis and monitoring components, which continuously provide system health status. Automated reasoning with constraint satisfaction form the core of our decision-making component, which assesses the current situation, aids in failure disambiguation, and constructs a contingency plan to mitigate the failure(s) and allow for a safe end of the mission. We will illustrate our contingency management system with two case studies, one for a fixed-wing aircraft in simulation, and one for an autonomous DJI S1000+ octo-copter

Haptic-Multimodal Flight Control System Update

The rapidly advancing capabilities of autonomous aircraft suggest a future where many of the responsibilities of today s pilot transition to the vehicle, transforming the pilot s job into something akin to driving a car or simply being a passenger. Notionally, this transition will reduce the specialized skills, training, and attention required of the human user while improving safety and performance. However, our experience with highly automated aircraft highlights many challenges to this transition including: lack of automation resilience; adverse human-automation interaction under stress; and the difficulty of developing certification standards and methods of compliance for complex systems performing critical functions traditionally performed by the pilot (e.g., sense and avoid vs. see and avoid). Recognizing these opportunities and realities, researchers at NASA Langley are developing a haptic-multimodal flight control (HFC) system concept that can serve as a bridge between today s state of the art aircraft that are highly automated but have little autonomy and can only be operated safely by highly trained experts (i.e., pilots) to a future in which non-experts (e.g., drivers) can safely and reliably use autonomous aircraft to perform a variety of missions. This paper reviews the motivation and theoretical basis of the HFC system, describes its current state of development, and presents results from two pilot-in-the-loop simulation studies. These preliminary studies suggest the HFC reshapes human-automation interaction in a way well-suited to revolutionary ease-of-use