Tutorials

Avionics and Space systems require the use of a real-time operating system (RTOS) in order to meet their timing constraints. This tutorial focuses on the RTEMS RTOS, a widely used RTOS in commercial, certified systems. RTEMS is a POSIX-compliant RTOS, developed by OAR for the US DoD in the ‘80s, and it is open source with a permissive license. It has been under active and continuous development ever since and has a large open source community. In addition to its open source nature, thanks to an effort supported by the European Space Agency (ESA), a fully open source pre-qualification package for the GR740 and GR712 processors from FrontGrade Gaisler is provided.

This course offers a detailed look at basic spacecraft avionics systems engineering and design processes and principals. All spacecraft avionics systems have similarities, but differ in many ways. This course addresses the up-front systems engineering process; requirement levels, trade studies, requirements allocation/linking requirements derivation, requirements verification, risk and risk assessment, safety, integration and test, costing, scheduling, and then applying all this to the avionics subsystem level design on a subsystem-by-subsystem basis. Attendees will be exposed to avionics subsystem designs that are typically used on satellite buses and will learn the terms, nomenclature and rules of thumb used in the development process. Each avionics subsystem is explained in detail to gain insight into manpower and cost requirements. In addition to spacecraft avionics equipment, the design, fabrication, and qualification of the electrical ground support equipment required for satellites are discussed in detail.

Aerial Experimentation and Research Platform for Advanced Wireless (AERPAW) is the first wireless communication research platform envisioned and built to allow studying the convergence of advanced wireless communication technologies (such as 5G) and autonomous drones. The platform became generally available to the public in November 2021. This tutorial introduces researchers to the AERPAW platform and its capabilities, enabling hands- on experimentation with wireless technologies and autonomous drones. Researchers who attend the tutorial will gain the skills to test their fundamental research ideas in a realistic outdoor wireless testbed.

This course provides a fundamental background in assured navigation for unmanned aircraft systems (UAS). It first introduces the various UAS/RPAS application domains and operational environments, UAS flight management and path planning, required performance parameters, and autonomy at the various levels of the Guidance, Navigation and Control function. Furthermore, it addresses the foundations of Global Navigation Satellite Systems (GNSS) and inertial navigation and discusses the challenges of operating in the various target environments with sole-means GNSS. Next, augmentation methods and alternative navigation methods will be discussed with a focus on guaranteeing required navigation performance in, especially, GNSS-challenged environments. Finally, the course will talk about the role of the navigation function in surveillance, geo-fencing and relative navigation in case of swarms of UAS.

In the latest years, sense and avoid (SAA), or detect and avoid (DAA), has represented one of the main roadblocks to the integration of unmanned aircraft systems (UAS) operations. This course outlines and reviews architectures, technologies, and algorithms for SAA. First, starting from a discussion about what constitutes a UAS and how it is different than manned aircraft, basic SAA definitions and taxonomies are discussed. Ground-based/airborne and cooperative/non-cooperative architectures are covered. The SAA process is dissected into its fundamental tasks, which are discussed in details. Different sensing algorithms and technologies are presented, including radar and optical systems. Potential and challenges of multi-sensor-based systems and data fusion are pointed out. Techniques for conflict detection, and approaches for remotely operated or autonomous avoidance are introduced. The tutorial ends with an overview of current perspectives and recent progress relevant to SAA for UAS integration in the Air Traffic Management (ATM) system and in the framework of UAS Traffic Management (UTM) / U-Space and Urban Air Mobility.  

The cyber threat landscape of aviation is increasing. Threats bring new security risks that are specific to aviation and impact public safety and well-being. This tutorial will introduce you to aviation cyber security, focusing on the aircraft at the center of an increasingly complex and technology-driven aviation ecosystem.

To securely build and defend your systems against attacks, it is essential to adopt the mindset of an adversary. This tutorial will enable you to do so and provide you a foundational understanding of cybersecurity principles and practices in the context of aviation. You will learn about ethical hacking and penetration testing methodologies and explore how they are used to identify and exploit vulnerabilities in computer systems and networks. Essential topics such as information gathering and reconnaissance, network scanning and enumeration, and system exploitation, along with some demonstrations are provided. Standards, legal and ethical frameworks and guidelines are also covered.

This tutorial aims to introduce participants to the critical aspect of product security in the aerospace environment. It will cover the motivation behind the need for product security, its definition, and the methods to address it within a company. Attendees will learn that the aspect of security nowadays does not only cover the protection of confidentiality, but expands in the aeronautical domain the additional upcoming challenge of airworthiness aspects as well as the assurance of the aircraft’s mission capability under adverse cyber conditions.

Artificial intelligence machine learning models used in aviation systems are growing with more use cases for edge and embedded use in real-time systems. Deployment for real-time systems edge use in aircraft and space systems requires rigorous performance and reliability testing of these models after initial architecture, training and validation is completed on scalable computing systems. Most often models must be quantized for embedded use, to reduce memory footprint and to reduce latency when used in avionics critical path solutions, and at the same time, the reliability of these models must be maintained.

With the recent uptake of interest in using Linux for safety applications (for example ELISA), tooling and infrastructure become more and more relevant. This tutorial will provide a hands-on experience for embedded Linux using the Nix meta build system and the NixOS Linux distribution. The attendees will configure a small Linux Kernel configuration and a traditional systemd based user-space using the Nix DSL. A minimal demo application will be incorporated, and the resulting system will be booted and inspected using QEMU.

There are avionics failures that most designers think can't happen, which actually can and do happen with probabilities far greater than requirements allow.  This lack of understanding leads to designs with insufficient dependability, which then contributes to accidents and incidents.  As one example, not understanding the Byzantine Generals Problem has led to $1B+ (yes, that's B for billion) in accident losses, incidents requiring avionics retrofit fixes, and a space shuttle launch scrub.  And yet, very few avionics designers understand the problem or how to create avionics designs that can tolerate it.  This tutorial gives some reasons why designers fail to believe in these real failures and what can be done to overcome this unfortunate situation.  Most of this tutorial will give examples of "incredible" failures that actually have happened.  This includes examples of:  Byzantine faults causing complete system failures, component transmogrifications, fault mode transformations (e.g. stuck-at faults that aren't so stuck), self-inflicted shrapnel, component creation via emergent properties, "evaporating" software, and exhaustively tested software that still failed.  As appropriate, many of these examples are accompanied by observations of how to avoid or mitigate any future similar failure(s).  The objective is for these to be "lessons learned and understood" rather than just "lessons observed".

Drones, particularly small and medium-sized rotary-wing drones, have rapidly become essential tools for a wide range of industries, including agriculture, surveillance, emergency response, law enforcement, and the military. Additionally, swarms of heterogeneous drones—encompassing UAVs, UGVs, USVs, and UXVs—are increasingly valuable for navigating environments with diverse and complex constraints, such as air, ground, surface, and underwater. Modern warfare has undoubtedly driven advancements in swarms technology, while artificial intelligence has played a crucial role in enabling their capabilities and enhancing their effectiveness in various applications.

This tutorial aims to provide participants with a comprehensive understanding of aircraft trajectory analysis using deterministic rule-based methods and machine learning techniques. Over the course of three hours, participants will learn how to access trajectory data, implement analysis techniques in Python, and design machine learning algorithms for more advanced studies. By the end of the tutorial, participants will acquire the necessary knowledge to analyse and interpret aircraft trajectories in diverse real-world scenarios.

As airborne systems become more and more complex – partly in order to “off load” aircrews, the certification of such systems becomes even more challenging, as the emphasis shifts from the complexity of human behavior to the even greater complexities of systems and software. More complex and sophisticated techniques, such as Artificial-Intelligence (AI) / Machine-Learning (ML) are now making their first steps into aviation safety-critical systems, both airborne and on the ground, and this trend is matched by new certification requirements presented by worldwide regulators such as the FAA and EASA.

GPUs are currently considered from all safety critical industries, including avionics and aerospace to accelerate general purpose computations and meet performance requirements of new advanced functionalities, which are not possible with the legacy, single-core processors used in these domains, such as in the recent Airbus project Automatic Taxi, Take- off and Landing (ATTOL) project. This tutorial aims to provide a basic understanding of GPU programming and the GPU architecture. Both aspects are required for the acceleration of high performance algorithms for new generation avionics and aerospace systems, and more importantly for their certification. The tutorial will focus on GPU programming using the CUDA programming language and will explain the Hardware Architecture of both NVIDIA GPUs as well as AMD GPUs, which are currently used in avionics systems mainly for graphics, but also considered for general purpose computing in the near future.

GPUs are currently considered from all safety critical industries, including avionics and aerospace to accelerate general purpose computations and meet performance requirements of new advanced functionalities, which are not possible with the legacy, single-core processors used in these domains, such as in the recent Airbus project Automatic Taxi, Take- off and Landing (ATTOL) project. However, most of the R&D is currently focused on proof of concepts, which demonstrate the capabilities of employing GPUs in avionics, ignoring the certification challenges introduced by GPUs. This tutorial is the outcome of years or research at Barcelona Supercomputing Center (BSC) and technology transfer within safety critical industries, which culminated in the recent approval of these methods (July 2022) from the competent airworthiness authority in Spain and soon by EASA, for the first time in Europe. The attendees will learn how general purpose GPU code can be developed and certified according to safety critical standards used in these industries by using graphics-based technologies (OpenGL SC 1.0.1 and 2.0) which have are already used in certified safety critical products of the highest criticality (DAL-A avionics according to DO-178C and ASIL D according to ISO 26262). This will include the latest GPU programming API for safety critical systems ratified by Khronos, Vulkan SC, in March 2022, which one of the organisers (Dr. Leonidas Kosmidis) has been one of the earliest adopters and helped to be defined by participating in its Khronos Vulkan Safety Critical Advisory Panel. Special attention will be paid on Brook Auto/BRASIL, an open source technology developed at BSC (https://github.com/lkosmid/brook), which abstracts away the complexities of programming in these graphics based solutions in a CUDA like language, while retaining their certification benefits, and have been demonstrated with industrial use cases. Finally, the tutorial will include a hands-on session with exercises, during which the attendees will have the opportunity to experiment with the certifiable solution(s) of their interest. BSC will provide remote access to relevant GPUs with preinstalled certifiable GPU languages/APIs.

seL4, the fastest, most correct, (likely) most complicated kernel on earth provides unmatched performance and security/safety guarantees. Being policy free, it also presents developers with a plethora of complicated technical decisions. Microkit, a thin abstraction layer on top of seL4, provides for a radical simplification, massively reducing the complexity of development on top of seL4. This session provides a hands-on experience on developing for the Microkit, based upon the existing Wordle Tutorial offered earlier in this tutorial program.

Traditional digital avionics systems have included ground and flight segments where the most intensive processing is often done on the ground for applications like optimization compared to more immediate lower latency requirements for flight control and flight management. Combined ground and embedded avionics are however being asked to do more based on exciting new uses of airspace from UAS to space- based ventures as well as expanding commercial, military and general aviation. New features may range from interactive agent and assistant features that enhance flight optimization and planning to new cybersecurity features for the post-quantum world.

Digital aviation systems designers are being asked to provide more sophisticated autonomous and semi-autonomous features for aerospace systems including general aviation and UAS much like automotive AV/ADAS (Autonomous Vehicle/Advanced Driver-Assistance Systems) is challenging automotive embedded systems.  Traditionally many of these systems have been modular AMP (Asymmetric Multi-Processing) systems that run simpler cyclic executives for hard real-time mission critical computation with clear separation via standardized interfaces from core flight control and management to less critical planning and convenience features.  New features may range from soft real-time or interactive assistant features that enhance flight optimization and planning to the more traditional mission critical flight control systems.  The drive to integrate assistant and autonomous features is a combined opportunity and challenge for embedded system hardware, firmware, and software systems engineering. 

The tutorial introduces several Air Traffic Management (ATM) initiatives envisioned by the Federal Aviation Administration (FAA) for a bold future airspace that combines conventional traffic and new entrants (e.g., drones) without sacrificing safety. In this framework, we demonstrate the use of state-of-the-art AI/ML modeling and prediction tools that will enable efficient and safe traffic flow in the U.S. National Airspace System (NAS). In particular, Natural Language Processing (NLP) tools can help extract data (e.g., airspace constraints) that are currently contained in legacy text and audio format and convert them into digital information. The digitized information can be ingested by route planning, arrival scheduling and other decision support tools both on the ground and in the flight deck.

In recent years, the market growth of the aviation sector has resumed its pre-pandemic trends, and a significant expansion of commercial space operations is being witnessed. The anticipated rise of commercial Unmanned Aircraft Systems (UAS) and Advanced Air Mobility (AAM) services at the lower end of the airspace, and of operations above Flight Level 600 and point-to-point high-speed transport at the other end are expected to compound these trends, challenging the viability of conventional Air Traffic Management (ATM) and airspace management paradigms. Concerning space operations, challenges linked to Space Domain Awareness (SDA) and space sustainability have also increased in the recent past, leading to the need of effective Space Traffic Management (STM) architectures supported by appropriate Communications Navigation and Surveillance technologies.