Papers
13
Total Citations
436
H-Index
12
About
Liefa Liao is a prolific robotics and control systems researcher whose work spans mobile robotics, autonomous vehicles, and intelligent control methodologies. With a primary focus on automated guided vehicles (AGVs), recurrent neural networks (RNNs), and bio-inspired optimization algorithms, Liao has established a distinctive research identity at the intersection of classical control theory and modern machine learning. His most cited contribution, "Tracking Control of Redundant Mobile Manipulator: An RNN Based Metaheuristic Approach" (2020, 91 citations), demonstrates his pioneering integration of neural computation with robotic motion planning. Complementing this, his work on RNN-based optimal motion control for mobile robots (2019, 48 citations) and PID optimization using PSO and BAS algorithms for AGVs (2022, 53 citations) highlights a sustained commitment to bridging theoretical frameworks with practical industrial applications. Liao's research portfolio also extends into quadrotor modeling, pipe inspection robotics, and service robot development — most notably the FOODIEBOT project (2024, 41 citations) — reflecting remarkable breadth. Collectively accumulating nearly 400 citations, his contributions offer both foundational reviews and innovative engineering solutions, making his work an invaluable resource for students and practitioners navigating the rapidly evolving field of autonomous robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4Design and Development of FOODIEBOT Robot: From Simulation to Design41 citations · 2024
- 5
- 6Review On: The Service Robot Mathematical Model32 citations · 2022
- 7
- 8
- 9
- 10PID Tuning Method on AGV (automated guided vehicle) Industrial Robot23 citations · 2019