- Based on instructors' AIAA textbook “The Anatomy of Autonomy” (2025)
- All students will receive an AIAA Certificate of Completion at the end of the course
OVERVIEW
Digital technology has become pervasive across virtually all of aerospace. Its influence has arguably been nowhere more significant than in its role of facilitating autonomous operations for a diverse array of aerospace systems. Whether the goal be to simplify, assist or even eliminate the role of the human pilot/operator, increasingly sophisticated autonomous capabilities are changing the face of aerospace –facilitating the expansion of flight and mission envelopes, enabling novel new vehicle designs, and creating new opportunities and markets. The Anatomy of Autonomy short course is structured to enable a fundamental understanding of autonomous capabilities, the foundations of their design, and their impact on current and future aviation and space systems. An elemental decision cycle representation is introduced as the universal building block underpinning autonomous task design and implementation. An ensuing discussion of the resulting architecture is used to explore the differences between traditional automation and more advanced perception-driven autonomy. That discussion also serves to expand the attendees’ understanding of more complex and capable autonomous systems, including their design and integration into aerospace systems, as well as the operational potential and limitations of those systems. Examples from both aviation and space realms are used to facilitate an understanding of the potential of autonomy to increase security, safety, performance, and economic potential within the aerospace domain. An introduction to contemporary artificial intelligence (AI) methods and practice sets the stage for understanding how these technologies will enable and enhance autonomous capabilities in aerospace systems. The issues and obstacles that inhibit the use of AI in aerospace are also discussed. Regulatory and legal precedents, institutional constraints, and other societal factors that lie beyond the technical domain are also addressed. The course is structured to convey the authors’ diverse perspectives on these topics, including technological, developmental, and operational viewpoints, enabling a better understanding of its past, current, and potential future roles for autonomy in aerospace vehicles, systems, and related infrastructure.
LEARNING OBJECTIVES
Upon completion of the course, the attendee should:
- Understand the value proposition for autonomy in aerospace systems.
- Gain an appreciation for the historical evolution of autonomous capabilities in aviation and space environments.
- Become familiar with autonomy levels and metrics used to describe autonomous capabilities.
- Understand the functional architecture that serves as the design basis for autonomous capability.
- Become familiar with those aviation and space applications that are serving as catalysts for the accelerated development of autonomous technologies and systems.
- Understand the opportunities afforded by increased autonomous capability as applied to aviation and space systems.
- Understand the limitations of classical automation in creating autonomous capability.
- Understand the importance, role, and complexity of task integration in increasingly autonomous systems and their operations.
- Understand the potential roles and limitations of employing artificial intelligence technologies to enable autonomy in both aviation and space applications.
- Gain a fundamental understanding of AI methods and their application to aerospace systems.
- Gain an appreciation of the evolving relationship between human stakeholders, especially pilots and operators, with increasingly autonomous aerospace capabilities.
- Understand the impact of autonomy on traditional areas of contemporary engineering practice.
- Become familiar with the challenges to autonomous system design development and implementation beyond the technical arena.
AUDIENCE
This course is intended for students and professionals seeking to understand the foundation and fundamentals of autonomous aerospace systems’ design, integration, and operations, including the past evolution and future potential for autonomy in aerospace. The course is particularly suited to those in the broader aerospace community having limited familiarity with these systems, their enabling technologies, and their potential to expand the flight and mission envelopes of crewed and uncrewed vehicles and their supporting systems.
- Recommended AIAA Text by the instructors: “The Anatomy of Autonomy” (2025)
COURSE FEES (Sign-In To Register)
- AIAA Member Price: $995 USD
- AIAA Student Member Price: $495 USD
- Non-Member Price: $1195 USD
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OUTLINE
1. Introduction and Overview
- Introductions – Instructors & Attendees
- Course Scope, Format and Objectives
- Course Overview
- Motivation for Autonomy in Aerospace
- Autonomy: The Big Picture
2. Autonomy Defined … Description & Measurement
- Definitions & Terminology
- Autonomy Metrics
- Levels of Autonomy – an Overview
- Autonomous Vehicle Mobility Management
- Mission-Level Autonomy
- Collaborative Autonomy
- Autonomous Contingency Management
- Technologies of Autonomy
- Autonomy in Aerospace Today
- Origins and Early History – Air & Space
- Inventions, Innovations, and Infrastructure
- Aviation
- The Space Age
- Modern Aerospace
- The Decision Cycle … the Functional Architecture of Autonomy
- Task Level Autonomy
- Autonomous Task Integration
- System Level Autonomy
- Supporting Hardware Systems & Attributes
- Expanded Architecture Perspectives
- The Decision Cycle Revisited
- Automation vs. Perception-driven Autonomy
- Information Gathering – Detect, Sense & Collect
- Making Sense of the Data – Integrate, Assess, and Evaluate
- Decisions – Determination & Application
- Acting on the Decision(s) – Execute, Implement
- ‘Intra-gration’ – Interactions Inside the Decision Cycle
- Toward Perception-driven Autonomy
- Evolution of Integrated Autonomous Capabilities
- Enabling Higher-Level Autonomy … Integration of Routine Tasks
- Advisory Systems and Decision Aids
- The Autonomous Mission Manager (AMM)
- Toward a System-of-Systems (SoS) AMM
- Contingency Management … Automating the ‘What-ifs?”
- Architectural Considerations and Design Challenges
- Integrated Vehicle Digital Flight Control with Vectored Thrust
- Launch Vehicle Staging
- The ‘Grocery Bot’
- Garmin Autoland
- Mars Entry, Descent & Landing
- Pilots & Astronauts
- Aviation Fundamentals – a Historical Perspective
- AVIATE, NAVIGATE, COMMUNICATE
- Classes of Aircraft and Operator Impact
- Crew Resource Management
- Roles and Responsibilities in Multi-pilot Aircraft
- Threat and Error Management
- Space Systems and their Evolution
- Operating in Space
- Space Race – Beginnings
- The Astronaut’s Role & Evolution
- The Emergence and Influence of Computing Power
- Space Operations in the Late 20th Century
- Crewed Space Systems in the Early 21st Century
- Flight Management Simplification
- Uncrewed Air Systems
- Optionally-Piloted Vehicles
- Advanced Air Mobility
- Air Traffic Management (ATM) & Deconfliction
- Space Operations, Commerce, and Exploration Shared Challenges
- Shared Challenges
- Overview
- Air Vehicles & Systems
- Space Vehicles & Systems
- Human-Autonomous Machine Interface
- Atmospheric Vehicles on Other Planetary Bodies … Ingenuity
- Orbital & Deep Space Operations
- Summary --- The Impact of Automation– An Operator’s Perspective
- Introduction … Expectations and Opportunities
- The Emergence of AI – Reality vs. Myth
- An AI Primer – Background & Definitions
- AI Concepts
- History of AI
- AI vs. Machine Learning
- Data and Data Management
- Algorithm Overview
- Algorithm Selection and Application
- The State-of-the-Art: Successes and Limitations
- AI Systems Example—The Grocery Bot Revisited
- Summary
- Legacy Avionics and Related Issues
- Software Complexity & Cost
- Testing – the Verification & Validation Dilemma
- Machine ‘Intelligence’ and Systems Engineering …
- Cyber-physical Security Considerations
- The Legal and Regulatory Environment
- Roles for AI in Aerospace Autonomy
- The Data – Access, Recency, Interpretation, and Trust
- AI Systems Example—The Mars Rover
- The Evolution of Data: Maps, traffic, weather, health, intent, and more
- Creating an AI Ecosystem for Aerospace
- The Path Ahead … Opportunities & Constraints
- Evolving Air and Space Environments
- The Influence of Emerging Technologies
- Opportunities – New Capabilities, Missions, Markets …
- Creating Trust – Paths to Certification of High-level Autonomy
- The Evolving Human-Machine Relationship
- The Broader Challenges Ahead
- Course Summary & Epilogue
INSTRUCTORS
Dr. Michael S Francis has been a pioneer in the development of uncrewed and autonomous systems, having initiated what became DARPA’s original Unmanned Combat Air Vehicle Program in the early 1990s. He joined DARPA while still on active duty as an Air Force Colonel to lead the award-winning US-German X-31 Enhanced Fighter Maneuverability (EFM) Demonstrator program through its flight test phase. X-31 was developed to break the aerodynamic stall barrier and demonstrate the value of post stall maneuvering in close in air combat … it was the first (and still only) international X-plane development. During that same period, Col. Francis initiated DARPA’s original Micro Air Vehicle (mAV) program, taking the concept of “uncrewed” to a whole new level. A decade later and following his military retirement, Dr. Francis served as the Director for the $4.5B DARPA-USAF-Navy Joint Unmanned Combat Air Systems (J-UCAS) Program. He has also served in executive roles at Aurora Flight Sciences, Lockheed Martin Corporate Headquarters, General Atomics and the United Technologies Research Center (UTRC). While at Aurora, he co-founded and served as the first president of Athena Technologies – a start-up control systems developer later acquired by Rockwell-Collins. At UTRC, he initiated and guided Sikorsky Aircraft’s initiative to develop autonomous systems for optionally-piloted and uncrewed helicopters. Francis holds B.S., M.S., and Ph.D. degrees in Aerospace Engineering Sciences from the University of Colorado. He is a Fellow of the AIAA and elected to the Connecticut Academy of Science and Engineering. He earned his private pilot license in 1964.
Professor Ella Atkins is Fred D. Durham Professor and Head of the Kevin T. Crofton Department of Aerospace and Ocean Engineering at Virginia Tech. She is a foremost authority on autonomous aerospace systems with research contributions to both aeronautical and space domains. She serves as the editor-in-chief of the AIAA Journal of Aerospace Information Systems. Before joining Virgina Tech, Dr. Atkins was a professor in the Department of Aerospace Engineering at the University of Michigan where she also served as the Director of the Autonomous Aerospace Systems Laboratory, and the associate director of the University of Michigan Robotics Institute. She began her academic career as an assistant professor of aerospace engineering at the University of Maryland, College Park. Dr. Atkins holds B.S. and M.S. degrees in Aeronautics & Astronautics from MIT. She earned M.S. and Ph.D. degrees in Computer Science and Engineering from the University of Michigan. Her dissertation was entitled “Plan Generation and Hard Real-time Execution with Application to Safe, Autonomous Flight”. Atkins is a Fellow of the American Institute of Aeronautics and Astronautics. In 2022, she was named as the recipient of the AIAA Intelligent Systems Award.
C.E. “Noah” Flood - Since his first flying lesson at age 12, Noah has devoted decades to his love of aviation, flying a variety of aircraft ranging from general aviation aircraft to military fighters to large commercial airliners. Bringing operational experience, creativity, critical thinking, and curiosity to Anatomy of Autonomy, he seeks to influence the future of autonomy in the aerospace arena. Noah shares insights from experiences as a Civil Air Patrol cadet, Fighter Weapons School graduate, and Chief Pilot and Line Check Airman at a major American airline to demonstrate the applicability of autonomy within the aerospace realm. A graduate of the U. S. Air Force Academy and University of Cincinnati College of Law, Noah’s practical experience includes tactical testing and evaluation of the High-Speed Anti-Radiation Missile (HARM), flight tests resulting in the Supplemental Type Certification of the GLU-2100 Multi-mode Receiver, serving in an Aviation Safety Action Program, and negotiating a multi-billion-dollar labor contract. He is a member of the District of Columbia Bar and the Association for Unmanned Vehicle Systems International (AUVSI). He served on the National Research Council, Aeronautics and Space Engineering Board’s Committee on Autonomy Research for Civil Aviation whose report is available through the National Academies Press. Noah has presented at the American Institute of Aeronautics and Astronautics SciTech and Aviation Forums and is a member of the Institute’s Advanced Air Mobility Certification Task Force. He is published in the Encyclopedia of Aerospace Engineering covering Social and Legal issues related to unmanned aircraft. As an amateur astronomer, Noah focuses his energy on the wonders of our Universe and its current exploration.
CLASSROOM HOURS / CEUs: 24 classroom hours / 2.4 CEU/PDH
CANCELLATION POLICY: On-demand course purchases are non-refundable.
CONTACT: Please contact Lisa Le or Customer Service if you have any questions about the course or group discounts.
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