Papers
8
Total Citations
82
H-Index
5
About
Yingchun Zhang’s research bridges robotics, control systems, and rehabilitation engineering, with a focus on intelligent path planning, fault diagnosis, and human–machine interaction. His early work on optimum path planning for mobile robots introduced a hybrid genetic algorithm with self-adaptive crossover and mutation probabilities, achieving over 40 combined citations and establishing a foundation for autonomous navigation. He extended this to appearance-based navigation using omnidirectional cameras and monocular structured light for pose determination of non-cooperative satellites, demonstrating versatility across terrestrial and space applications. In control theory, Zhang developed robust fault reconstruction methods for discrete-time Lipschitz nonlinear systems using Euler-approximate proportional integral observers, advancing safety in sampled-data systems. More recently, his contributions to stroke rehabilitation are notable: he showed that botulinum toxin treatment can improve myoelectric pattern recognition in robot-assisted therapy, and his pilot study on muscle synergy-guided exercise through human–machine interaction demonstrated improved neuromuscular coordination and reduced motor impairment. These works, published in 2024–2025, signal a growing impact in neurorehabilitation. With over 80 total citations across diverse fields, Zhang’s career reflects a commitment to translating control and robotics innovations into practical solutions for mobility and recovery.
Research Focus
Key Achievements
Top Papers
- 1Optimum Path Planning for Mobile Robots Based on a Hybrid Genetic Algorithm25 citations · 2006
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- 3Optimum Path Planning for Mobile Robots Based on a Hybrid Genetic Algorithm17 citations · 2006
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- 7Appearance-based mobile robot navigation using omnidirectional camera4 citations · 2012
- 8The influence of common component on myoelectric pattern recognition3 citations · 2020