Sheng-Pi Huang
Papers
1
Total Citations
5
H-Index
1
About
Sheng-Pi Huang’s research lies at the intersection of robotics, computer vision, and intelligent grasping systems, with a focus on enabling home service robots to interact more naturally with their environments. His most cited work, “A 3D vision based object grasping posture learning system for home service robots” (2017), introduces a novel approach that allows robots to recognize object orientation and select feasible grasping points by analyzing surrounding spatial constraints. This contribution addresses a critical challenge in autonomous manipulation—how to adapt grasping strategies when initial planned postures prove inadequate. By integrating 3D vision with adaptive learning, Huang’s system enhances robotic dexterity and reliability in unstructured domestic settings. Although his citation count is modest, the work demonstrates foundational impact in applied robotics, particularly for service applications where precision and adaptability are paramount. Huang’s research advances the practical deployment of vision-guided manipulation, offering a pathway toward more capable and intuitive home assistant robots.
Research Focus
Key Achievements
Top Papers
- 1