Developing students’ capabilities to understand, utilize, and improve state-of-the-art robotic systems with embedded control systems  

Robotic systems powered by embedded control systems, particularly humanoid robots, robotic arms, and quadrupedal robots (e.g., robotic dogs), have gained significant traction across industries, including healthcare, manufacturing, and service sectors. However, undergraduate students often lack exposure to and hands-on experience with these cutting-edge technologies, limiting their ability to understand, utilize, and innovate within this rapidly evolving field. The current related courses focus on foundational concepts of embedded systems and programming skills, with a limited practical component centered on automatic guided vehicles (AGVs), which falls short of equipping students with the skills needed to engage with state-of-the-art robotic systems and their embedded control applications. To address this gap, the course MNE358 Embedded Control Systems will be improved to focus on the design, control, and optimization of robotic systems, with an emphasis on humanoid robots, robotic arms, and quadrupedal platforms. Through a combination of theoretical instruction and practical exercises, students will explore the core principles of embedded control systems, including real-time processing, sensor integration, actuator control, and communication protocols. The course will introduce interactive, hands-on learning methods and materials, enabling students to engage directly with these robotic systems. A comprehensive project manual and example cases will guide students in applying embedded control systems to solve real-world challenges, such as robotic arms assembly, teleoperation, autonomous navigation, and precision manipulation. Additionally, a library of project topics will be developed to inspire students to brainstorm, investigate, and iterate their own robotic designs, fostering innovation and problem-solving skills. Furthermore, the integration of AI technologies, such as machine learning and computer vision, will enable students to develop smarter, adaptive robotic systems capable of autonomous decision-making and complex task execution in dynamic environments. By integrating these advanced robotic platforms into the curriculum, MNE358 will bridge the gap between theoretical knowledge and practical application, preparing students to understand, utilize, and improve modern embedded control systems. This transformation ensures students are equipped with the critical competencies needed to thrive in industries increasingly reliant on intelligent robotic systems and contribute to the rapidly evolving field of robotics and embedded control systems.