Kanrun Huang
Papers
1
Total Citations
3
H-Index
1
About
Kanrun Huang is a robotics researcher whose work sits at the intersection of 3D perception, object modeling, and robotic manipulation. Their most notable contribution focuses on the challenge of building accurate 3D object models in real time during robotic manipulation tasks — a problem with significant practical implications for autonomous systems operating in unstructured environments. In their 2019 paper, "Building 3D Object Models during Manipulation by Reconstruction-Aware Trajectory Optimization," Huang addresses how robots can leverage object shape information — both global structure and local surface geometry — to improve grasping strategies and navigate cluttered scenes without unintended contact. The core insight is that trajectory planning and 3D reconstruction need not be treated as separate pipelines; instead, robot motion can be actively optimized to gather the most informative views for shape recovery. While still an emerging body of work with 3 citations, this research tackles a foundational challenge in embodied AI and manipulation robotics. Huang's contributions represent a meaningful step toward robots that can intelligently perceive and interact with novel objects in dynamic, real-world settings.
Research Focus
Key Achievements
Top Papers
- 1