UAV Design: Foundations of Cyber-Physical Systems

Master the foundations of UAV design, cyber-physical systems, and autonomous control

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About

UAV Design: Foundations of Cyber-Physical Systems

Step into the world of intelligent aerial systems and discover how drones are transforming modern technology. This course takes you on a complete journey from the basic design and operation of UAVs to the advanced computing and networking methods that make them smart, connected, and autonomous. We begin with the foundations: frames, motors, sensors, flight controllers, and the logic of modular, open platforms that make upgrades and experimentation easy. From there, you'll learn how drones communicate over air-to-air and air-to-ground links, compare Wi-Fi and cellular (4G/5G) paths, and see when to use directional antennas, relays, or mesh networking for reliable coverage.

You'll then explore how drones collect, process, and share data using onboard computing, edge AI, and high-speed communication. Through clear explanations and real examples, you'll see how distributed computing, coordinated control, and 5G connectivity enable missions like search-and-rescue, inspection, mapping, and multi-UAV cooperation. We'll also connect communication and control through co-design principles: reinforcement-learning-based antenna alignment, swarm coordination, mobility models for safe airspace sharing, and practical strategies to reduce latency and energy use while maintaining link quality.

The final module focuses on airborne computing and AI: selecting Jetson/Intel boards, using containers and virtualization (Docker/KVM), and scaling intelligence across fleets with federated and coded computing. Each module builds on the last starting with drone architecture, moving through communication systems and control, and culminating in advanced edge computing and AI for resilient swarms. Whether you're an engineering student, researcher, or drone enthusiast, this course equips you with the knowledge to understand, evaluate, and build next-generation UAV technologies that compute, communicate, and collaborate in the real world.

What You'll Learn

  • Fundamentals of UAV systems: quadrotors vs. fixed-wing UAVs, flight controllers, sensors, and onboard computing
  • The concept of an Open Airborne Computing Platform modular design for research and prototyping
  • Basics of UAV communication: air-to-air and air-to-ground links, Wi-Fi vs. cellular networks, directional antennas
  • Networking opportunities and challenges: latency, bandwidth limits, energy constraints, safety, and regulations
  • Virtualization & Containers (Docker, KVM) for UAV computing flexibility and security
  • Control and Co-Design: how communication and control must work together, including reinforcement learning solutions for antenna alignment
  • Distributed UAV computing: swarm intelligence, coded computing, and federated learning
  • Real-world applications: disaster recovery, emergency communications, agriculture, inspection, drone swarms, and smart cities

Prerequisites

  • Basic understanding of computer networks and programming (Python/C++ helpful but not mandatory)
  • Familiarity with electronics or embedded systems is useful but not required
  • No prior experience with drones is needed — the course will guide you from fundamentals to advanced topics

Who This Course Is For

  • Students in Electrical, Electronics, Computer, or Aerospace Engineering curious about UAVs
  • Researchers exploring autonomous systems and cyber-physical computing
  • Drone enthusiasts interested in advanced UAV technologies
  • Anyone excited about the future of drones, flying taxis, and smart city integration

This course includes 4 comprehensive video modules, 4 quizzes, and certificates of completion.

Meet Your Instructors

Learn from leading experts in UAV systems and cyber-physical computing

Dr. Yan Wan

Distinguished University Professor, Electrical Engineering

University of Texas at Arlington

Specializes in cyber-physical systems, networked control systems, and multi-agent coordination. Research focuses on intelligent UAV systems for disaster response and infrastructure monitoring.

Dr. Junfei Xie

Professor, Department of Electrical and Computer Engineering

San Diego State University

Specializes in unmanned aerial systems, artificial intelligence, and large-scale dynamical networks. Research focuses on cyber-physical systems, networked airborne computing, and stochastic modeling and control for autonomous and intelligent UAV systems. His work also addresses airborne networks, air traffic flow management, and complex information systems for scalable autonomous operations.

Dr. Kejie Lu

IEEE Senior Member, Professor, Department of Computer Science and Engineering

University of Puerto Rico, Mayagüez

Focuses on computer and communication networks, including network architecture, protocol design, performance evaluation, and security. His research also covers wireless communications, space-time coding, and channel capacity analysis, contributing to robust and high-performance communication frameworks for UAV and distributed networked systems.

Dr. Shengli Fu

Professor, Department of Electrical Engineering

University of North Texas

Research interests include modulation, coding, and information theory, with strong emphasis on wireless communications and sensor networks. His work spans cooperative communications, distributed networks, and pattern recognition, including audio and visual signal processing, supporting reliable and efficient communication systems for modern networked and airborne platforms.

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