Yukyu Chan
Papers
1
Total Citations
6
H-Index
1
About
Yukyu Chan is a pioneering researcher in robot manipulation and haptic sensing, whose work focuses on enabling robots to perceive and interpret physical interactions through touch. In their most-cited study, "Effects of Force-Torque and Tactile Haptic Modalities on Classifying the Success of Robot Manipulation Tasks" (2019, 6 citations), Chan systematically investigated which haptic sensing modalities—from wrist-mounted force-torque sensors to tactile feedback—most effectively allow robots to determine task success. This foundational research has significant implications for improving robotic dexterity and autonomy in real-world applications like manufacturing and assistive robotics. By comparing and combining different haptic inputs, Chan’s work provides critical insights into sensor fusion strategies, helping robots better understand their environment through touch. Though early in their career, Chan’s contributions are already shaping how researchers approach haptic feedback in manipulation, offering a clear path toward more intuitive and reliable robotic systems. Their work stands out for its practical focus on classifying task outcomes, a key step toward fully autonomous robots that can adapt to complex, unstructured environments.
Research Focus
Key Achievements
Top Papers
- 1