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About

Jianran Liu is a leading researcher in the field of robotic vision and human-robot interaction, with a primary focus on high-speed perception and intelligent decision-making for table tennis robots. His work centers on enabling robots to understand and respond to human opponents in real time, bridging the gap between machine vision and dynamic sports. Liu’s most significant contribution is a visual-based method for estimating an opponent’s hitting behavior, which enhances a robot’s predictive capabilities and responsiveness—a paper that has garnered 30 citations. He also developed a high-speed vision system capable of processing images at 200 frames per second, along with a novel ball trajectory reconstruction algorithm, cited 14 times. Notably, Liu pioneered the fusion of vision and inertial measurement unit (IMU) data to track a player’s racket trajectory in real time, offering deep insights into human habits during play. His adaptive color-space detection method for racket pose and neural-network-based stroke modeling further demonstrate his innovative approach to robotic perception and control. With a cumulative impact spanning over 50 citations, Liu’s work is essential reading for researchers in robotics, computer vision, and intelligent sports systems.