Vincent Lim
Papers
2
Total Citations
52
H-Index
2
About
Vincent Lim is a robotics researcher whose work sits at the intersection of manipulation, dynamics, and self-supervised learning. His primary research focus is on enabling robots to dynamically manipulate deformable objects—specifically cables—to extend their functional workspace beyond traditional kinematic limits. Lim’s most significant contribution is the introduction of **Planar Robot Casting (PRC)**, a novel task where a single planar motion of a robot arm holding one end of a cable causes the free end to slide across a surface toward a desired target. This approach allows robots to reach points far beyond their physical workspace, with direct applications in cable management and industrial automation. To solve this challenging dynamic task, Lim developed a **Real2Sim2Real self-supervised learning framework**, which bridges the gap between simulation and reality without requiring extensive real-world data. His work has garnered over 50 citations, with his 2022 paper receiving 39 citations alone. By combining physics-based simulation with data-driven policy learning, Lim has demonstrated how robots can learn complex, high-speed manipulation skills autonomously. His research represents a key step toward more dexterous and adaptive robotic systems capable of handling the messy, dynamic realities of physical environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2Planar Robot Casting with Real2Sim2Real Self-Supervised Learning13 citations · 2021