Tse-Ching Lai

Tamkang University

Papers

1

Total Citations

13

H-Index

1

About

Tse-Ching Lai is a robotics researcher whose work centers on path planning and obstacle avoidance for robotic manipulators. His most-cited paper, "Path planning and obstacle avoidance approaches for robot arm" (2017, 13 citations), introduces a novel method leveraging Non Uniform Rational B-splines (NURBS) to ensure safe, collision-free motion. In this contribution, Lai proposed a safety formula for NURBS weights that maintains a critical safe distance between the robot arm's end-effector and obstacles, directly addressing a fundamental challenge in industrial and service robotics. This work provides a computationally efficient framework for real-time trajectory adjustment, enhancing the reliability of autonomous robotic systems in cluttered environments. While his citation count reflects a focused, early-career impact, Lai's approach to integrating geometric modeling with safety constraints offers a practical solution for improving robot autonomy. His research contributes to the broader goal of enabling robots to operate safely alongside humans, a key priority in modern robotics. For students and researchers exploring motion planning, Lai's work demonstrates how mathematical tools like NURBS can be adapted to solve real-world robotic challenges.

Research Focus

Key Achievements

1
H-Index
1
Papers
13
Total Citations
13
Avg Citations/Paper
🏆 Most Cited Paper
Path planning and obstacle avoidance approaches for robot arm
13 citations · 2017
📈 Most Prolific Year: 2017 (1 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: Tamkang University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 11 days ago