Papers
16
Total Citations
639
H-Index
9
About
Dianye Huang is a robotics researcher whose work spans intelligent robot control, robotic perception, and medical robotics. His early and most influential contributions focus on advanced control schemes for robot manipulators, particularly addressing trajectory tracking under output error constraints and input saturation. His 2020 paper on neural control of robot manipulators has accumulated 282 citations, establishing him as a notable voice in barrier Lyapunov function-based and composite learning control methodologies. Complementing this, his work on adaptive dynamic programming and admittance control demonstrates a sustained interest in optimal, interaction-aware robot behavior. More recently, Huang has expanded into robotic perception and embodied AI, contributing MonoGraspNet, a framework enabling 6-DoF grasping from a single RGB image, and SG-Bot, a scene-graph-driven object rearrangement system. A growing thread in his research addresses robotic ultrasound imaging, where he has published on pulsation-aware artery segmentation, deep venous thrombosis examination, and a comprehensive review of machine learning in robotic sonography. Together, his portfolio reflects a researcher bridging rigorous control theory with modern data-driven approaches, with meaningful applications in both industrial robotics and clinical healthcare settings.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3MonoGraspNet: 6-DoF Grasping with a Single RGB Image42 citations · 2023
- 4Machine Learning in Robotic Ultrasound Imaging: Challenges and Perspectives41 citations · 2024
- 5
- 6Model predictive optimization for imitation learning from demonstrations19 citations · 2023
- 7
- 8
- 9
- 10