Teaching
Learning By Doing & Learning Together
Learning By Doing & Learning Together
It aims to teach basic computer programming with hands-on tools, such as Microprocessors for C language, mobile robot platforms for ROS/C++ with ROS programming, or Unity for C# with VR or AR devices, Students will learn how to utilize the programming skills by controlling various hands-on tools.
It aims to teach advanced scientific skills for developing autonomous systems to build a testbed for robotics experiments. Students will learn how to design robots using 3D CAD programs, fabrication machines such as milling, CNC, 3D printers, and electronics. As well, they will learn how to make printer circuity boards (PCBs) using Eagle cad, then build the sensor monitoring system
It aims to teach the basic structure and application of various middleware, such as the Robot Operating System (ROS), Lab Streaming Layer (LSL), and a Real-Time Operating System (RTOS). Students will develop overall system frameworks using middleware to manipulate various sensors, actuators, and other components simultaneously.
It aims to teach AI technology, covering machine learning, deep learning, and reinforcement learning. Students will apply these AI algorithms to mobile robots, such as for predicting robot loss of control from sensor data, making prediction algorithms from open-source datasets, and building model-free robot controllers using various learning models.
It aims to teach basic knowledge about theory construction, model building, and human factors in the field of HRI. Students will learn social science theories that can be applied to HRI, then build a computational algorithm to apply their theories, models, and human factors to solve real-world HRI problems.
Textbook: "Theory Construction and Model-Building Skills" & "Human factors in simple and complex systems"