Chun-Yu Chai
Papers
2
Total Citations
12
H-Index
2
About
Chun-Yu Chai is a robotics researcher specializing in perception and manipulation for challenging, real-world environments. His work addresses critical limitations in robotic vision, particularly for objects that confound standard sensors—such as black, transparent, reflective, and texture-less items. In his highly cited 2020 paper, "Deep Depth Fusion," Chai pioneered a method to combine structured-light and stereo camera data, overcoming their individual failure modes to produce robust point clouds for robotic grasping. This work has garnered 8 citations for its practical impact on industrial and service robotics. Chai also advanced the field of object rearrangement with his 2020 study on "Adaptive Unknown Object Rearrangement Using Low-Cost Tabletop Robot." He developed a novel planning algorithm that enables robots to manipulate completely unknown objects without pre-defined models or manual intermediate targets, achieving the task through adaptive, single-step interaction predictions. This contribution, with 4 citations, demonstrates his focus on creating more autonomous and versatile robotic systems. By tackling fundamental perception and planning challenges, Chai is building the foundation for robots that can operate reliably in unstructured, everyday settings.
Research Focus
Key Achievements
Top Papers
- 1
- 2Adaptive Unknown Object Rearrangement Using Low-Cost Tabletop Robot4 citations · 2020