Papers
3
Total Citations
15
H-Index
2
About
Fulong Yin is a robotics researcher whose work focuses on whole-body control for legged and wheeled robots, bridging the gap between biological motion and robotic locomotion. His key research areas include learning-based control, model simplification, and hierarchical optimization for complex robotic systems. Yin’s most cited paper, "Run Like a Dog: Learning Based Whole-Body Control Framework for Quadruped Gait Style Transfer" (2021, 9 citations), introduces a novel framework that enables quadruped robots to mimic real animal gaits, using a low-level controller for torque calculation and a high-level neural network for style transfer—a significant step toward more natural robotic movement. In "Reduced-Dimensional Whole-Body Control Based on Model Simplification for Bipedal Robots With Parallel Mechanisms" (2025, 4 citations), he tackles the challenge of controlling bipedal robots with parallel mechanisms, proposing a reduced-dimensional controller that balances model accuracy with real-time performance. His work on "Hierarchical Optimization-Based Hybrid Whole-Body Control for Wheel-Legged Robots" (2025, 2 citations) further extends these principles to hybrid platforms. Yin’s contributions are advancing the field of legged robotics, making robots more agile, efficient, and biologically inspired.
Research Focus
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Top Papers
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