Fadi Rafeedi — accepted AI-conference papers

2025

Cycloidal Quasi-Direct Drive Actuator Designs with Learning-Based Torque Estimation for Legged Robotics

Alvin Zhu, Yusuke Tanaka, Fadi Rafeedi, Dennis W. Hong

ICRA 2025

This paper presents a novel approach through the design and implementation of Cycloidal Quasi-Direct Drive actuators for legged robotics. The cycloidal gear mechanism, with its inherent high torque density and mechanical robustness, offers significant advantages over conventional designs. By integra

Cited by 6 Source ↗Scholar ↗

2021

Design and Control of a Novel Compact Nonlinear Rotary Magnetic SEA (MSEA) for Practical Robotic Gripper Implementation

Fadi Rafeedi, Jeong H. Yoon, Dennis W. Hong

RA-L 2021

In this letter we present a novel design of a nonlinear series elastic actuator based on magnetic repulsive forces. The primary application of the actuator is for simple robotic grippers that operate in close proximity to the environment and are exposed to hazards of collision frequently. The design

Cited by 5 Source ↗Scholar ↗