Robotics & Haptics Systems
This course introduced the fundamentals of robotics, haptic systems, and real-time control through a series of progressively more advanced hardware and software projects. Working with the Hapkit and GraphKit platforms, I developed embedded firmware, implemented kinematic models, designed force-feedback algorithms, and built interactive visual interfaces to explore human-machine interaction.
The course culminated in a final project where my teammate and I developed a two-degree-of-freedom haptic handwriting guidance system for motor rehabilitation. Our project received the Best Demonstration Award, recognizing both the technical implementation and user experience.
GraphKit Handwriting Guidance System
View my Final Project Report
For the final project, my teammate and I developed GraphKit, a two-degree-of-freedom haptic handwriting guidance system designed to assist motor learning and rehabilitation. The system combined embedded firmware, forward kinematics, Jacobian-based force mapping, and a Processing-based graphical interface to guide users through handwritten characters using real-time force feedback. The software supported the complete English alphabet, a Chinese character benchmark, and automatically recorded user accuracy and completion time for performance evaluation.
The project integrated mechanical design, embedded systems, robotics, and controls into a single platform operating at a 120 Hz control loop. Through experimental testing, we demonstrated measurable improvements in handwriting accuracy with haptic guidance enabled, and the project was recognized with the Best Demonstration Award for its technical implementation and user experience.
Leader–Follower Haptic Device
One of the first projects in the course focused on developing a real-time leader–follower haptic system using two Hapkit devices. The objective was to create a low-latency control architecture where the motion of a leader device was accurately replicated by a follower device through bidirectional communication between embedded microcontrollers.
I developed the embedded firmware in Arduino to interface with AS5600 magnetic encoders, implement real-time position tracking, and communicate with a Processing-based visualization environment. The project introduced key concepts in haptic control, including sensor integration, motor control, serial communication, and closed-loop feedback, while emphasizing the importance of timing and stability in real-time robotic systems.
Tactile Feedback & Virtual Environments
Building on the Hapkit platform, I implemented a series of haptic rendering algorithms capable of simulating virtual environments through force feedback. By modeling virtual walls, springs, dampers, and surface interactions, the device was able to generate realistic tactile sensations using only motor torque and position feedback.
This project introduced the principles of kinesthetic haptics, impedance control, and virtual environment rendering. Through iterative tuning of control parameters and real-time visualization in Processing, I gained experience developing intuitive human-machine interfaces that translated mathematical models into physical user interactions.