Sijiang Liu
Papers
11
Total Citations
185
H-Index
9
About
Sijiang Liu is a leading researcher in advanced robotic and hybrid manufacturing systems, with a focus on precision machining, trajectory planning, and intelligent control. His work addresses critical challenges in robotic machining, including chatter suppression, feedrate optimization, and adaptive grinding. Liu’s most cited paper, “A jerk-limited heuristic feedrate scheduling method based on particle swarm optimization for a 5-DOF hybrid robot” (2022, 48 citations), introduces a novel approach to smooth, high-speed motion control. He also pioneered “Chatter-free and high-quality end milling for thin-walled workpieces through a follow-up support technology” (2023, 32 citations), offering a practical solution to vibration in flexible workpiece machining. With over 180 total citations, Liu’s contributions span dynamic parameter identification, constant force control, and collision-free trajectory generation. His work on dual-robot mirror milling and robotic friction stir welding demonstrates a strong commitment to real-world industrial applications. Liu’s research is highly influential for students and engineers seeking to improve robot accuracy, efficiency, and adaptability in complex manufacturing environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5
- 6
- 7
- 8
- 9
- 10