Papers
12
Total Citations
85
H-Index
6
About
Petros Daras is a leading researcher at the intersection of computer vision, robotics, and artificial intelligence, with a primary focus on developing intelligent systems for industrial and environmental applications. His most impactful work centers on hybrid human-robot collaboration for recycling and disassembly, particularly addressing the urgent global challenge of e-waste. Daras pioneered novel frameworks for human-robot collaborative recycling plants, as demonstrated in his highly cited 2019 paper, which proposes a hybrid environment for processing electrical and electronic equipment. He has also made significant contributions to visual object detection and recognition, advancing robust feature matching techniques through innovations like Kendall's rank correlation measure for SIFT-based matching, and developing viewpoint-independent object recognition in cluttered scenes. His research extends to object affordance reasoning from RGB-D videos, enabling robots to understand human-object interactions. With multiple papers accumulating over 16 citations each, Daras has demonstrated substantial impact in both fundamental computer vision and applied robotics. He has also contributed to the field through editorial work on artificial intelligence and human movement, and by organizing benchmark challenges like the SHREC 2020 track on 6D object pose estimation, further solidifying his role as a key figure in advancing vision-enhanced robotic systems for manufacturing and environmental sustainability.
Research Focus
Key Achievements
Top Papers
- 1
- 2Robust SIFT-based feature matching using Kendall's rank correlation measure16 citations · 2009
- 3
- 4
- 5Joint Object Affordance Reasoning and Segmentation in RGB-D Videos7 citations · 2021
- 6
- 7
- 8
- 9
- 10SHREC 2020 Track: 6D Object Pose Estimation3 citations · 2020