Angelo Ciulla
Papers
1
Total Citations
3
H-Index
1
About
Angelo Ciulla is a robotics researcher whose work bridges the gap between human motion and robotic imitation. His primary research focuses on human-robot interaction, particularly the use of low-cost, accessible sensors to enable intuitive control and learning in humanoid platforms. His most cited work, "A Kinect-Based Gesture Acquisition and Reproduction System for Humanoid Robots" (2020), demonstrates a practical system that captures human gestures using a Microsoft Kinect sensor and translates them into executable motions for a humanoid robot. This contribution is significant for making robot programming more accessible, reducing the need for complex manual coding or expensive motion-capture equipment. While his citation count is currently modest, the work represents a foundational step in democratizing robotic gesture learning—a critical area for assistive robotics and collaborative manufacturing. Ciulla’s research is particularly valuable for students and engineers seeking cost-effective, real-world solutions for teaching robots new skills through demonstration.
Research Focus
Key Achievements
Top Papers
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