Yuh-Ren Chien
Papers
2
Total Citations
41
H-Index
2
About
Yuh-Ren Chien is a researcher whose work centers on computational geometry and collision detection, a critical area for robotics, computer graphics, and virtual simulation. His major contributions lie in developing more accurate and efficient methods for detecting collisions between convex polyhedra in three-dimensional space. Chien’s key innovation is the simultaneous use of both enclosing and enclosed ellipsoids to represent objects, a technique that significantly improves upon traditional methods that rely solely on bounding ellipsoids. This dual-ellipsoid approach allows for a more precise estimation of distance and potential contact, reducing false positives and computational overhead. His most cited work, "A novel collision detection method based on enclosed ellipsoid" (2002), has garnered 27 citations, while its predecessor from 2001 has 14 citations. These papers have laid important groundwork for fast and accurate collision detection in graphical simulation environments, making Chien’s contributions valuable for researchers and engineers developing interactive 3D systems, path planning algorithms, and physically realistic simulations.
Research Focus
Key Achievements
Top Papers
- 1A novel collision detection method based on enclosed ellipsoid27 citations · 2002
- 2Fast and accurate collision detection based on enclosed ellipsoid14 citations · 2001