Andrea Pilco
Papers
5
Total Citations
15
H-Index
3
About
Andrea Pilco is a rising researcher in the intersection of robotics and computer vision, with a focus on deep learning-driven automation. Her work centers on integrating YOLO-based object detection algorithms with robotic systems to enhance real-time perception and manipulation. Pilco’s major contributions include developing hand gesture recognition for human-robot interaction, color classification and sorting using YOLOv5 on both 3-DOF robotic arms and mobile platforms, and joint angle estimation for industrial manipulators via convolutional detection and K-means clustering. She has also pioneered a restricted area sign detector for mobile robots, improving privacy and efficiency in delivery tasks. With her most-cited paper, “Human-Robot Interaction Based on Hand Gesture Detection Using YOLO Algorithm,” already accumulating 5 citations in 2025, Pilco is demonstrating early-career impact. Her work is notable for its practical applications in industrial automation, healthcare logistics, and safe human-robot collaboration. By combining accessible deep learning models with real-world robotic tasks, Pilco is contributing to the next generation of intelligent, vision-guided autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2Color Classification Using a 3-DOF Robotic Arm Based on the YOLOv5 Model3 citations · 2024
- 3Color Sorting System Using YOLOv5 for Robotic Mobile Applications3 citations · 2024
- 4
- 5Restricted Area Sign Detector Using YOLO v52 citations · 2023