Shanzeng Liu
Papers
1
Total Citations
2
H-Index
1
About
Shanzeng Liu is a robotics researcher whose work focuses on the control and motion planning of underactuated robotic systems—machines with fewer actuators than degrees of freedom, which pose unique challenges in stability and maneuverability. His most cited paper, "Obstacle Avoidance of a Class of Underactuated Robot Manipulators: GA based approach" (2008), introduces a practical, collision-free motion planning method by first analyzing the dynamic properties of these manipulators and then reformulating obstacle avoidance as a position-based force control problem. This genetic algorithm-driven approach offers a novel solution for navigating complex environments without full actuation control. While his citation count of 2 reflects a niche but specialized contribution, Liu’s work contributes foundational insights into the intersection of underactuated dynamics and intelligent optimization, relevant for advancing autonomous manipulation in constrained settings. His research is particularly valuable for students and engineers exploring non-traditional control strategies in robotics, where efficiency and adaptability are paramount.
Research Focus
Key Achievements
Top Papers
- 1