Yinhao Liang

About

Yinhao Liang is a leading researcher in intelligent robotics, specializing in human–robot interaction, kinematic calibration, and cognitive control systems. His work addresses critical challenges in Industry 4.0, enabling robots to adapt dynamically to their environments. Liang’s most cited paper, "Online Robot Kinematic Calibration Using Hybrid Filter With Multiple Sensors" (2020, 61 citations), pioneers real-time parameter correction, moving beyond traditional offline methods to enhance robot versatility. He further advances precision with "A Cognitive Joint Angle Compensation System Based on Self-Feedback Fuzzy Neural Network With Incremental Learning" (2020, 34 citations), which reduces joint angle errors through adaptive learning—a key contribution to industrial accuracy. Liang also innovates in human–robot collaboration, developing a gesture-based interface with unrestricted force feedback (2022, 15 citations) and an active collision avoidance system for human safety (2020, 11 citations). His markerless interface with vibration feedback (2019) integrates multi-sensor tracking for intuitive teleoperation. With over 120 total citations, Liang’s work bridges theoretical advances and practical applications, making him a notable figure in robotics research.

Research Focus

Key Achievements

Top Papers

1. 1
   Online Robot Kinematic Calibration Using Hybrid Filter With Multiple Sensors

   61 citations · 2020
2. 2
   A Cognitive Joint Angle Compensation System Based on Self-Feedback Fuzzy Neural Network With Incremental Learning

   34 citations · 2020
3. 3
   A Gesture-Based Natural Human–Robot Interaction Interface With Unrestricted Force Feedback

   15 citations · 2022
4. 4
   Active Collision Avoidance for Human-Manipulator Safety

   11 citations · 2020
5. 5
   Markerless Human-Manipulator Interface with Vibration Feedback Using Multi-sensors

   3 citations · 2019

Key Collaborators

Contact & Links