Lung-Shan Tsai
Papers
1
Total Citations
6
H-Index
1
About
Lung-Shan Tsai is a robotics researcher whose work centers on the intersection of nonlinear control, motion planning, and obstacle avoidance for complex mechanical systems. His most-cited paper, "A nonlinear programming approach to nonholonomic motion planning with obstacle avoidance" (2002), introduces an innovative algorithm that leverages geometric phase concepts and path integrals along m-polygons to generate optimal, collision-free trajectories for nonholonomic systems—such as wheeled robots or spacecraft—operating in cluttered environments. By framing path planning as a nonlinear programming problem, Tsai provided a rigorous mathematical foundation for solving one of robotics' most persistent challenges: steering systems with non-integrable velocity constraints safely around obstacles. While his citation count (6) reflects a focused, specialized contribution rather than broad impact, the work remains a valuable reference for researchers tackling constrained motion planning. Tsai's approach stands out for its elegant synthesis of geometric mechanics and optimization, offering a principled alternative to heuristic or sampling-based methods. For students and researchers exploring nonholonomic robotics, his paper serves as a concise yet powerful demonstration of how nonlinear programming can yield practical, provably optimal solutions to real-world navigation problems.
Research Focus
Key Achievements
Top Papers
- 1