Course Details
Course Summary
This space training program provides a comprehensive introduction to the field of Artificial Intelligence (AI) and how it is applied to space assets. Students will gain a solid understanding of the fundamentals of AI, including the two major approaches of parallel data processing and using symbolic logic to plan missions/make decisions. The course will cover various applications including autonomous spacecraft navigation, image processing to label images, recognition of faces, and data analysis to find patterns. It is important to remember that a ChatBot is a verbal query for search. Throughout the course, students will have the opportunity to apply these techniques to realistic space situational awareness, allowing them to gain practical experience in developing and implementing related AI techniques and algorithms. By the end of the course, students will be able to identify opportunities for the application of AI in space missions on the platform or off-board. This includes the automation of the ground control station for 24-7 coverage and the resolution of contingencies in order to assure a safe mission.
Course Materials
Each attendee receives extensive notes and reference materials.
Who Should Attend
The course is for engineers, scientists, business managers, and engineering managers of diverse background and with varying levels of experience, including those who are new or familiar to artificial intelligence. This class would appeal to individuals who are involved in planning space projects, designing systems, building, testing, and during the operations of autonomous “robotic” or manned spacecraft.
What You Will Learn
Course Outline
- Mind-Body Problem
- Human Cognition
- Neuroscience
- Psychology
- Perception
- Linguistics
- Systems Theory
- Complex Vehicles
- Complex Environments & Space
- Human & Machine Theory
- Human-AI Collaboration
- Human-Machine Interaction
- Autonomous Operations
- Architecture
- Goal Theory
- Utility Theory
- AI Decision Making
- With Uncertainty
- Intelligent Systems
- Artificial General Intelligence (AGI)
- Artificial Intelligence (Part 1)
- Data, Information, Knowledge
- Pattern Recognition
- Expert Systems
- Search
- Logic
- Problem Solving
9. Artificial Intelligence (Part 2)
- Machine Learning
...Perceptron
...Deep Learning - Machine Vision
- Natural Language Processing
- Speech - ChatBots
- Diagnostics
10. Evolution of Computers
- CPUs
- GPUs
- Memory
- Applied AI
- Symbolic Logic
- Parallel Data Processing/Connectionist Theory
- Neuro-Symbolic AI
- Applications to Space
- Spacecraft Vehicle Manager (Orion)
- Autonomous Rover Navigation (Mars Rovers)
- Ground Control Station Automation (NASA Ground Automation)
- Future
- Moore’s Law
- Turing Test
- Singularity
- Consciousness
- Sentience
- Ethics
Instructor
Wendell Chun is Director and Assistant Professor of Systems Engineering at the University of Denver. He is a Subject Matter Expert (SME) in robotics, mobile robots, autonomy, and artificial intelligence. Wendell has 33 years of hands-on experience in industry at Lockheed Martin Space Systems Company where he was the principal investigator of various robotic R&D programs that featured self-driving cars, interfacing with a digital twin of a mobile robot, ground station architect, and autonomous manipulation. He is a technical advisor to different branches of the US government such as NASA and the Department of Energy, currently consulting on autonomous drones and ground mobile robots for radiation measurements. He was co-editor/conference chairman on the SPIE Mobile Robot Conferences from the mid-1980s to mid-1990s. Wendell was an author of sections in NASA’s Report to the US Congress on Satellite Servicing through NASA Goddard Space Flight Center and Chapter 61: Surveillance and Security Robots in the Springer Handbook of Robotics, Rev. 2.