Session 1

The Future of Robotics

Machines That Move, Sense, and Adapt

What makes a robot smart? Students explore the technologies behind the next generation of robots and intelligent devices, learning how sensors, cameras, embedded computers, and software work together to help machines understand and respond to the world around them. Hands-on projects introduce the building blocks of modern robotics through programming, sensing, and experimentation.

Using Python and C/C++, students investigate computer vision, image processing, environmental sensing, and artificial intelligence while exploring applications in robotics, healthcare, smart homes, environmental monitoring, and other emerging technologies.

Curriculum

Students work with embedded computer systems, sensors, cameras, and programming tools to explore how hardware and software combine to create intelligent robotic systems. Using Python and C/C++, students develop applications involving computer vision, image processing, motion and object detection, and machine intelligence.

Projects introduce environmental sensing and data collection as students build systems that monitor conditions such as temperature and humidity, analyze sensor data, and display information in real time. Students also explore how artificial intelligence and computer vision allow robots and smart systems to classify images, recognize objects, and respond to information from their surroundings.

Throughout the program, students strengthen their programming, engineering, robotics, teamwork, and communication skills. Team projects and demonstrations provide opportunities to design, test, troubleshoot, and present intelligent systems while exploring the expanding applications of modern robotics.

mobile robots
Planned Topics
  • Embedded computer systems and smart sensing technologies
  • Sensors for temperature, humidity, motion, and other environmental conditions
  • Python and C/C++ programming for robotic systems
  • Computer vision and image processing with OpenCV
  • Motion and object detection
  • Image classification and visual recognition
  • Collecting, analyzing, and visualizing sensor data
  • Artificial intelligence and machine intelligence in robotics
  • Connecting sensors, software, and hardware into intelligent systems
  • Applications in healthcare, environmental monitoring, smart homes, and emerging technologies
  • Designing, testing, and troubleshooting robotic systems
  • Team project demonstrations and technical communication
     

 

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Dongbin Lee
Faculty Lead
Don Lee

Assistant Professor, ECPE (SOECS)

Ph.D., Clemson University, 2009

Dr. Dongbin "Don" Lee is an assistant professor in the ECPE department in the School of Engineering and Computer Science at Pacific. He has expertise and interest in uncrewed robotic systems with control systems and AI/deep/machine learning techniques in application to self-driving autonomous vehicles, smart manufacturing, efficient solar-power systems, farmers-centered sustainable precision agriculture tech, vector control, EOD, drones and ATVs. Dr. Lee advises the solar-powered racing car club, builds student-centered projects at Pacific, advises student competition teams including robotics and supports STEM/MESA outreach. In addition, he was the recipient of several Oregon NASA space grants between 2017 and 2022.

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