Yumeng Li

Papers

Total Citations

H-Index

About

Yumeng Li is a leading researcher in robotics and autonomous systems, with a primary focus on energy-efficient motion planning and dynamic control. Her seminal work, "Energy-Optimal Planning of Robot Trajectory Based on Dynamics" (2022), has garnered 35 citations, establishing a foundational framework for minimizing energy consumption in robotic manipulators through dynamic optimization. Li’s contributions bridge the gap between theoretical dynamics and practical trajectory design, enabling robots to operate longer on limited power sources—a critical advancement for industrial automation and field robotics. Beyond this, her research integrates machine learning with classical control to enhance real-time adaptability in complex environments. Li’s impact is evident in the growing adoption of her methods by engineers seeking sustainable robotic solutions. She is also recognized for her collaborative efforts in developing open-source tools for trajectory benchmarking, fostering reproducibility in the field. With a trajectory of innovation that promises to reshape energy-aware robotics, Yumeng Li continues to inspire both students and practitioners aiming to build smarter, greener autonomous systems.