Jinghao Hu

Shaoxing University, Northwest University

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About

Jinghao Hu is a researcher at the intersection of robotics, artificial intelligence, and computer vision, with a primary focus on enabling machines to perceive and evaluate human-like motion aesthetics. His key research areas include robotic motion planning, visual aesthetics evaluation, and point cloud registration for 3D perception. Hu’s most notable contribution is his work on “Multiple Visual Feature Integration Based Automatic Aesthetics Evaluation of Robotic Dance Motions” (2021, 19 citations), where he developed a novel framework that allows robots to autonomously assess the aesthetic quality of their dance movements by mimicking human self-observation—a significant step toward more natural and expressive human-robot interaction. This work bridges the gap between low-level motion control and high-level aesthetic cognition, offering a pathway for robots to learn from visual feedback much like human dancers. More recently, Hu introduced “IOPCNet” (2025, 3 citations), an innovative point cloud registration method that tackles the challenging problem of aligning 3D scans with low overlap rates, enhancing robotic perception in cluttered environments. Through these contributions, Hu is advancing the field of embodied AI, where robots not only move but also critically evaluate and refine their actions.