Papers
11
Total Citations
202
H-Index
5
About
Yujiang Xiang is a computational biomechanics and robotics researcher whose work bridges physics-based human motion modeling, exoskeleton design, and human-robot collaboration. His foundational 2010 review on optimization-based approaches to simulating human walking (137 citations) established him as a key voice in predictive biomechanical simulation, providing researchers and engineers with a comprehensive framework for understanding locomotion through computational methods. Building on this foundation, Xiang has made significant contributions to redundant dynamic systems, developing concurrent motion planning and reaction load distribution methods that address the complex interplay between human movement and environmental constraints. In recent years, Xiang has directed his expertise toward powered exoskeletons and human-robot collaborative systems, exploring optimal control strategies for knee and elbow exoskeletons to assist with physically demanding tasks such as lifting. His work on human-robot collaborative lifting — integrating 3D human arm models with robotic arm dynamics and validating grasping force predictions experimentally — represents a particularly cohesive research thread. More recently, he has incorporated markerless motion capture and multimodal perception to advance safe, adaptive human-robot interaction. Across these contributions, Xiang's research consistently demonstrates rigorous mathematical modeling paired with experimental validation, making his work valuable to students and practitioners in biomechanics, rehabilitation engineering, and robotics alike.
Research Focus
Key Achievements
Top Papers
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- 5Design Human-Robot Collaborative Lifting Task Using Optimization7 citations · 2021
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