Yihang CHEN

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About

Yihang Chen is a leading researcher in robotics and intelligent control systems, with a focus on optimal trajectory planning for robotic manipulators. His most-cited work, "Time Optimal Trajectory Planning Algorithm for Robotic Manipulator Based on Locally Chaotic Particle Swarm Optimization" (2022), has garnered 49 citations, addressing a fundamental challenge in robotic motion. Chen pioneered the integration of segmented polynomial interpolation functions with a locally chaotic particle swarm optimization (LCPSO) algorithm, significantly improving the efficiency and precision of time-optimal trajectories for robotic arms. This contribution enhances real-time motion control in manufacturing and automation, reducing operational delays while maintaining accuracy. His research bridges computational intelligence and mechanical systems, offering scalable solutions for complex robotic tasks. Chen’s work is widely recognized for advancing swarm intelligence applications in engineering, and his algorithm has been adopted in adaptive control systems. With a growing citation impact, he continues to shape the field of robotic motion planning, inspiring students and researchers to explore bio-inspired optimization in autonomous systems.