Papers
1
Total Citations
10
H-Index
1
About
Lei Pang is a researcher in robotics and computer vision, with a primary focus on developing intelligent grasping systems for cluttered and obstacle-filled environments. Their most-cited work, "A Vision-Based Robotic Grasping Approach under the Disturbance of Obstacles" (2018, 10 citations), introduces a novel pipeline that integrates deep learning-based object detection with Euclidean cluster extraction to enable robots to accurately identify and segment target objects amidst visual interference. This contribution addresses a critical challenge in autonomous manipulation—how to maintain reliable grasping performance when obstacles partially obscure or disrupt the robot’s view. By combining state-of-the-art object detection with robust point-cloud segmentation, Pang’s approach enhances the adaptability of robotic systems in real-world settings, such as warehouse automation or assistive robotics. While their citation count reflects an emerging career, the work demonstrates a clear impact on practical vision-guided robotics, offering a foundation for future studies in occlusion-aware grasping. Pang’s research sits at the intersection of deep learning, sensor fusion, and robotic control, making it relevant for students and engineers seeking to bridge perception and action in complex physical environments.
Research Focus
Key Achievements
Top Papers
- 1A Vision-Based Robotic Grasping Approach under the Disturbance of Obstacles10 citations · 2018