Papers
10
Total Citations
368
H-Index
6
About
Haohui Huang is a leading researcher in bio-inspired robotics and intelligent control systems, with a focus on enabling robots to achieve human-like motor learning and compliant interaction. His work bridges neuroscience and robotics, particularly through the development of broad learning adaptive neural control frameworks that allow robots to generalize skills naturally, as demonstrated in his highly cited 2019 paper (160 citations). Huang’s major contributions include optimal robot-environment interaction using broad fuzzy neural networks (157 citations), robust passivity-based dynamical systems for compliant motion adaptation, and impedance learning strategies that enhance robotic dexterity in unstructured environments. His research has profound implications for smart manufacturing, medical robotics, and human-robot collaboration. Notably, his recent work on image-driven imitation learning for robotic ultrasound systems (2025) and the IntuiGrasp dexterous hand showcase his commitment to translating biological principles into practical robotic applications. With over 350 cumulative citations, Huang’s innovative control methodologies have set new standards for adaptive, compliant, and intelligent robotic systems, making him a pivotal figure in advancing autonomous robot capabilities for real-world tasks.
Research Focus
Key Achievements
Top Papers
- 1Motor Learning and Generalization Using Broad Learning Adaptive Neural Control160 citations · 2019
- 2Optimal Robot–Environment Interaction Under Broad Fuzzy Neural Adaptive Control157 citations · 2020
- 3Robust Passivity-Based Dynamical Systems for Compliant Motion Adaptation14 citations · 2022
- 4A Compliant Force Control Scheme for Industrial Robot Interactive Operation12 citations · 2022
- 5
- 6Broad Fuzzy Neural Control Using Impedance Learning7 citations · 2019
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- 8
- 9Grasp Detection under Occlusions Using SIFT Features2 citations · 2021
- 10IntuiGrasp: Bio-Inspired Dexterous Hand with Intuitive Teaching1 citations · 2025