Jingtao Xue

Beijing Institute of Technology, Ministry of Education of the People's Republic of China

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Total Citations

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About

Jingtao Xue is a researcher advancing the intersection of robotics, embodied AI, and humanoid locomotion. His work spans three core areas: robotic manipulation, humanoid joint design, and intelligent navigation. In his early career, Xue tackled fundamental challenges in robotic control—developing a hand-eye 3D pose estimation system for a drawing robot (2013, 4 citations) that enables precise visual servoing for end-effector positioning, and proposing a dual-motor joint model (2013, 3 citations) to enhance driving force for fast humanoid walking. He also explored biologically inspired control with a muscle-model-based joint controller (2013, 2 citations), aiming to simplify autonomous motion in unknown environments. More recently, Xue has contributed to embodied AI through ReVoLT (2023, 3 citations), a framework that combines relational reasoning with Voronoi local graph planning for target-driven navigation in domestic settings. This work reflects his shift toward integrating reasoning and planning for efficient object search. While his citation counts are modest, Xue’s research demonstrates a consistent thread of practical innovation—from low-level joint mechanics to high-level navigation—showing a researcher committed to bridging hardware and intelligence in robotics.