Papers
3
Total Citations
12
H-Index
3
About
Sangjin Bae is a robotics researcher focused on advancing human-robot interaction and legged locomotion through innovative control strategies. His work spans three key areas: robot-aided rehabilitation, low-cost actuation, and quadruped robot dynamics. In his 2019 paper on robot-aided isokinetic exercise, Bae introduced the "exercise-as-desired" control scheme, enabling human intention-based muscular training—a significant step toward personalized rehabilitation robotics. His 2020 work on transparent torque sensor-less impedance rendering addressed a critical challenge in low-cost direct drive motors, proposing a method to achieve high-fidelity force interaction without expensive sensors, making advanced haptic feedback more accessible. Most recently, in 2024, Bae explored the Spring-Loaded Inverted Pendulum (SLIP) model for quadruped robot control, demonstrating that robust, high-performance locomotion can be achieved through simple dynamic principles rather than complex optimization or reinforcement learning. With over 12 citations across his most-cited works, Bae’s research bridges theoretical dynamics and practical implementation, offering elegant, cost-effective solutions for rehabilitation robotics and agile legged systems.
Research Focus
Key Achievements
Top Papers
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- 3SLIP Embodied Robust Quadruped Robot Control3 citations · 2024