Max Robotics — Global Service Robot Directory + US Certification

About

Minchang Sung’s research sits at the intersection of wearable sensing, assistive robotics, and advanced kinematic modeling, with a focus on restoring function for individuals with high-level limb loss. His most cited work introduces a wearable fabric sensor that classifies foot postures to control myoelectric hand prostheses—a breakthrough for amputees with shoulder disarticulation or transhumeral amputations who lack sufficient upper-limb muscle sites for conventional sEMG control. This paper has garnered 16 citations and demonstrates his commitment to practical, user-centered solutions. Sung also developed a knitted data glove system for finger motion classification, using conductive yarns to create a comfortable, sensor-integrated garment. On the theoretical side, he has contributed to robotic manipulation through an algorithmic Modified Denavit–Hartenberg modeling method using line geometry, and proposed an impedance control design framework that leverages a commutative map between SE(3) and se(3) for compliant six-degree-of-freedom interaction. With publications spanning 2019 to 2025, Sung’s work bridges soft wearable electronics and rigorous robot control theory, offering both immediate assistive applications and foundational advances in manipulation.