Luxuan Li
Papers
1
Total Citations
9
H-Index
1
About
Luxuan Li is a researcher whose work lies at the intersection of robotics, tactile sensing, and machine learning, with a particular focus on enabling more dexterous and reliable robotic manipulation. Their most notable contribution is a pioneering approach to slip detection for stable grasping, detailed in their 2017 paper "Learning to detect slip for stable grasping" (9 citations). This work introduced a novel hybrid method that combines unsupervised and supervised learning, using window matching pursuit to extract features from tactile data—a technique that significantly improves a robot's ability to maintain a secure grip on objects. By addressing a critical bottleneck in robotic manipulation, Li's research has direct implications for industrial automation, prosthetics, and human-robot interaction. Though early in their career, Li's work has already been recognized as an important basis for advancing the operation level of robots, demonstrating a clear talent for integrating computational methods with real-world physical challenges. Their research continues to push the boundaries of how robots perceive and interact with their environment.
Research Focus
Key Achievements
Top Papers
- 1Learning to detect slip for stable grasping9 citations · 2017