This Creative Inquiry research project investigates how Embodied AI technologies can innovate and enhance manufacturing through intelligent collaboration with human workers. Embodied AI agents—also known as interactive agents—are smart systems that perceive, learn, and act within their environment through a physical form, such as robots or augmented reality devices. The students gain hands-on experience in researching and developing innovative technologies that are shaping the future of smart manufacturing.

This course introduces the fundamental concepts of Agentic AI computing and its integration into robotic and automotive systems. Key topics include agentic frameworks, memory, context engineering, tool utilization, and interaction with environments and humans in simulated and real-world settings. The course emphasizes practical methodologies for integrating, developing and deploying AI agents for robot and automotive applications.

• Robot Learning
• Agentic AI Frameworks
• Agent Evaluation
• Vibe Coding and Tool Use
• Interaction with Environments&Human
• Simulation and Applications with Robot/Automotive Systems

This course will introduce the fundamental technologies for autonomous vehicle sensors, perception, and machine learning, from electromagnetic spectrum characteristics and signal acquisition, vehicle extrospective sensor data analysis, perspective geometry models, image and point cloud processing, to machine/deep learning approaches. We will also have hands-on programming experience in vehicle perception problems through homework and class projects.

• Electromagnetic spectrum characteristics and 1D Radar signal processing;
• Visual perception using 2D image processing and machine learning recognition;
• 3D LiDAR and point cloud data representation and processing;
• Visual/LiDAR/IMU for vehicle simultaneous localization and mapping (SLAM);
• Deep learning for vehicle perceptual sensor data processing.