Heng Lai
Papers
1
Total Citations
8
H-Index
1
About
Heng Lai is a researcher in robotics and computer vision, with a focus on visual perception for autonomous manipulation. His most-cited work, "Visual Robotic Object Grasping Through Combining RGB-D Data and 3D Meshes" (2016), has garnered 8 citations and addresses a critical challenge in robotics: enabling robots to grasp objects reliably in unstructured environments. By fusing RGB-D sensor data with 3D mesh models, Lai’s approach enhances the accuracy of object recognition and pose estimation, bridging the gap between raw sensory input and actionable robotic control. This contribution is particularly valuable for applications in industrial automation, service robotics, and human-robot interaction, where robust grasping is essential. While his citation count reflects a focused, early-career impact, the work demonstrates a clear technical contribution to the integration of geometric and visual data—a growing area in robotic perception. Lai’s research underscores the importance of combining multiple data modalities to achieve more reliable and adaptive robotic systems, making his work a useful reference for students and researchers exploring grasping and manipulation in real-world settings.
Research Focus
Key Achievements
Top Papers
- 1