Alexander Yu Tse
Papers
1
Total Citations
2
H-Index
1
About
Alexander Yu Tse is a researcher whose work lies at the intersection of robotics, tactile sensing, and perception. His primary research focus is on developing algorithms to extract rich contact information from vision-based tactile sensors—a critical challenge for enabling robots to perceive object properties during physical interaction. His most-cited paper, "Effective Estimation of Contact Force and Torque for Vision-based Tactile Sensor with Helmholtz-Hodge Decomposition" (2019), introduces a novel approach that leverages Helmholtz-Hodge decomposition to estimate both force and torque from tactile data. This contribution is significant because it moves beyond simple contact detection to provide richer, more actionable feedback for robotic manipulation tasks. Though his citation count is still growing, Tse's work addresses a foundational problem in tactile sensing: translating visual deformations into meaningful physical parameters. By tackling this challenge, he is helping to bridge the gap between raw sensor data and the high-level understanding robots need for dexterous interaction. His research is particularly relevant for applications in soft robotics, teleoperation, and autonomous grasping, where precise tactile feedback is essential.
Research Focus
Key Achievements
Top Papers
- 1