Pedro Furelos
Papers
1
Total Citations
2
H-Index
1
About
Pedro Furelos is a researcher at the intersection of cognitive robotics and real-time computer vision, with a focus on enabling machines to perceive and interact with dynamic environments. His most-cited work, "An Approach to 3D Object Detection in Real-Time for Cognitive Robotics Experiments" (2022), introduces a novel framework that balances computational efficiency with detection accuracy, allowing robots to identify and track objects in three dimensions during live experiments. This contribution is critical for advancing autonomous systems that require rapid, reliable perception—such as collaborative robots in manufacturing or assistive robots in human-centric settings. While his citation count is still growing, Furelos’s work stands out for its practical emphasis on real-time performance, bridging the gap between theoretical computer vision models and deployable robotic systems. His research is particularly relevant for students and engineers exploring cognitive architectures, sensor fusion, or embodied AI, as it provides a scalable solution for integrating 3D perception into resource-constrained platforms. Furelos’s approach underscores the importance of marrying algorithmic innovation with hardware constraints, a key challenge in modern robotics.
Research Focus
Key Achievements
Top Papers
- 1