Punit Tiwan
Papers
1
Total Citations
11
H-Index
1
About
Punit Tiwan’s research lies at the intersection of computer vision and robotics, with a particular focus on pose estimation and object manipulation in cluttered environments. His most-cited work, “Cylindrical Pellet Pose Estimation in Clutter using a Single Robot Mounted Camera” (2013, 11 citations), introduces innovative methods for determining the position and orientation of cylindrical pellets using a single camera mounted on a robot arm. This paper tackles the challenging problem of pose estimation in both isolated and occluded settings, comparing pellet contours from segmented images to achieve robust results. Tiwan’s contributions are especially relevant for industrial automation and robotic grasping, where accurate perception in messy, real-world scenarios is critical. By enabling a robot to estimate an object’s pose with minimal hardware, his work reduces complexity and cost in manufacturing and logistics. While his citation count reflects a focused, early-career impact, the practical significance of his methods continues to inspire further research in vision-based robotic manipulation. Tiwan’s approach demonstrates a keen ability to solve fundamental perception challenges that bridge the gap between laboratory setups and real-world applications.
Research Focus
Key Achievements
Top Papers
- 1