A. Zampetis
Papers
1
Total Citations
28
H-Index
1
About
Dr. A. Zampetis is a researcher specializing in robotic manipulation and machine vision, with a focus on enabling robots to handle complex, irregularly shaped parts in unstructured environments. Their most cited work, "A Machine Learning Approach for Visual Recognition of Complex Parts in Robotic Manipulation" (2017, 28 citations), tackles the critical challenge of part localization and grasping uncertainty. By integrating machine learning services for visual recognition, Zampetis developed a method that allows robotic systems to identify and manipulate components despite variable positioning and gripper instability—a key bottleneck in industrial automation. This contribution has been cited by peers working on adaptive robotics and computer vision, reflecting its practical relevance. Zampetis’s research bridges the gap between perception and action, offering scalable solutions for manufacturing and assembly tasks. Their work underscores a commitment to advancing autonomous systems that can operate reliably in real-world settings, making them a notable voice in the field of intelligent robotics.
Research Focus
Key Achievements
Top Papers
- 1