N. Urrestilla-Anguiozar
Papers
1
Total Citations
15
H-Index
1
About
N. Urrestilla-Anguiozar is a leading researcher in intelligent robotics and human-robot collaboration, with a focus on bridging the gap between human dexterity and industrial automation. Their most-cited work, "Transferring Human Manipulation Knowledge to Industrial Robots Using Reinforcement Learning" (2019, 15 citations), addresses a critical challenge in Industry 4.0: enabling robots to adapt flexibly to rapid market changes. By leveraging reinforcement learning to transfer human manipulation skills to robotic systems, Urrestilla-Anguiozar has pioneered methods that allow industrial robots to learn complex tasks without extensive manual programming. This work directly tackles the need for greater manufacturing flexibility, reducing downtime and increasing adaptability in dynamic production environments. Their contributions have been recognized for advancing the practical deployment of learning-based robotics in real-world industrial settings, offering a scalable pathway for robots to acquire new skills from human demonstration. With a growing citation impact, Urrestilla-Anguiozar’s research continues to influence the fields of robot learning, human-robot interaction, and smart manufacturing, making them a key figure in the evolution of adaptive, intelligent automation systems.
Research Focus
Key Achievements
Top Papers
- 1