Yezhang Li
Papers
1
Total Citations
5
H-Index
1
About
Yezhang Li is a researcher advancing the field of robotic control and automation, with a focus on intelligent manipulation systems. Their key research areas include model predictive control (MPC), robotic arm kinematics, and computer vision integration for autonomous grasping. Li’s major contribution lies in developing a novel MPC framework for a 3-DOF robot arm that optimises input torques by leveraging spatial coordinate recognition from monocular camera data. This work, published in 2023 and garnering 5 citations, demonstrates a practical approach to enabling precise object grasping through real-time colour and depth perception. By bridging control theory with vision-based perception, Li addresses critical challenges in industrial and service robotics, enhancing accuracy and adaptability in dynamic environments. Their notable achievement includes the successful implementation of a system that combines low-cost visual sensing with advanced predictive control, making sophisticated automation more accessible. Li’s research offers valuable insights for students and engineers exploring the intersection of control systems and robotics, highlighting the potential of MPC in real-world applications.
Research Focus
Key Achievements
Top Papers
- 1