Sejong | Biomechatronics Laboratory

Embedded Systems is a project-based course where students integrate sensing, control, and communication technologies to develop practical embedded devices. Throughout the semester, students gain hands-on experience with microcontrollers, HAL libraries, GPIO, ADC/DAC, timers, and serial communication protocols such as UART and CAN.

The course introduces students to core concepts in motor control using PWM and PID, and culminates in a team-based project where students design and build a closed-loop control system using sensors (e.g., Hall sensors), motor drivers (e.g., H-bridge), and embedded programming. The goal is to transform theoretical knowledge into working embedded systems capable of real-time actuation based on sensor feedback.

In the final class session, teams demonstrate their PID-controlled motor systems live in front of the class. Each system is evaluated in real-time using a standardized testing platform to measure position control accuracy. A contest-style ranking is conducted based on control performance, encouraging both technical excellence and friendly competition.

Embedded Systems is a project-based course where students integrate sensing, control, and communication technologies to develop practical embedded devices. Throughout the semester, students gain hands-on experience with microcontrollers, HAL libraries, GPIO, ADC/DAC, timers, and serial communication protocols such as UART and CAN.

The course introduces students to core concepts in motor control using PWM and PID, and culminates in a team-based project where students design and build a closed-loop control system using sensors (e.g., Hall sensors), motor drivers (e.g., H-bridge), and embedded programming. The goal is to transform theoretical knowledge into working embedded systems capable of real-time actuation based on sensor feedback.

In the final class session, teams demonstrate their PID-controlled motor systems live in front of the class. Each system is evaluated in real-time using a standardized testing platform to measure position control accuracy. A contest-style ranking is conducted based on control performance, encouraging both technical excellence and friendly competition.

Embedded Systems is a project-based course where students integrate sensing, control, and communication technologies to develop practical embedded devices. Throughout the semester, students gain hands-on experience with microcontrollers, HAL libraries, GPIO, ADC/DAC, timers, and serial communication protocols such as UART and CAN.

The course introduces students to core concepts in motor control using PWM and PID, and culminates in a team-based project where students design and build a closed-loop control system using sensors (e.g., Hall sensors), motor drivers (e.g., H-bridge), and embedded programming. The goal is to transform theoretical knowledge into working embedded systems capable of real-time actuation based on sensor feedback.

In the final class session, teams demonstrate their PID-controlled motor systems live in front of the class. Each system is evaluated in real-time using a standardized testing platform to measure position control accuracy. A contest-style ranking is conducted based on control performance, encouraging both technical excellence and friendly competition.

Sensors and Actuators is a theory-centered course that provides students with a comprehensive understanding of how physical quantities are measured and converted into control signals, and how those signals drive mechanical motion in mechatronic systems. Based on William Bolton’s “Mechatronics”, the course explores the operating principles of diverse sensors—including mechanical, thermal, optical, and electromagnetic types—and the transduction mechanisms that enable analog phenomena to be expressed in electrical form.

Students also study a wide range of actuator technologies such as DC motors, solenoids, stepper motors, and pneumatic or hydraulic actuators. Emphasis is placed on how energy conversion, torque generation, and motion control are achieved through these devices, and how actuators are selected based on performance requirements such as precision, speed, and force. The course also covers the signal conditioning and amplification processes necessary to interface sensors and actuators with digital control systems.

By the end of the semester, students will be able to explain the fundamental physics behind sensing and actuation, analyze transducer characteristics, and understand how sensors and actuators are integrated within feedback control systems. The course builds a strong theoretical foundation for practical applications in Embedded Systems, Robotics, and Automation Engineering, bridging the gap between physical dynamics and electronic control.

Advanced AI and Robotics Convergence- Biomechatronics of Movement is a project-based course that integrates biomechanics, neurophysiology, and mechatronic control to explore how human motion can be analyzed, modeled, and enhanced through engineering principles. Students examine the structure and function of the musculoskeletal system, focusing on how biological sensing, actuation, and feedback control inspire modern robotic and rehabilitation systems. The course provides a unified framework connecting human movement science with biomechatronic design.

Throughout the semester, students gain practical experience with musculoskeletal modeling and simulation using tools such as OpenSim, learning how to analyze joint torques, muscle activations, and motion dynamics. Core topics include muscle modeling, inverse and forward dynamics, and the principles of motor control and optimization. Students also discuss how these models inform the development of wearable and assistive robotic systems capable of supporting or restoring human movement.

In the final phase of the course, teams apply the learned concepts in a simulation-based project using OpenSim Moco. Each group formulates and solves an optimal control problem to reproduce or enhance a target movement, translating theoretical understanding into quantitative simulation results. The projects are presented in the final session, where teams demonstrate their control strategies and compare performance metrics, reinforcing both theoretical insight and practical competence in biomechatronic system design.