About

Manuel Lopes is a leading researcher at the intersection of robotics, cognitive development, and human-robot interaction. His work centers on how robots can learn autonomously through intrinsic motivation, curiosity, and interaction with their environment—a key contribution to developmental robotics. Lopes is best known for his foundational role in the iCub humanoid robot project, an open-source platform designed to study human cognition (606 citations). He has made seminal contributions to the theory and application of affordances, showing how robots can learn the relationships between actions, objects, and effects to enable prediction, planning, and imitation (354 and 112 citations). His research on intrinsic motivation and curiosity has shaped modern approaches to open-ended learning in artificial agents (377 citations). Lopes has also advanced multimodal attention systems, sound localization for humanoids, and ergonomic human-robot collaboration. With over 2,000 citations across his most influential works, his research has had a lasting impact on how robots develop cognitive skills through self-exploration and social guidance, bridging machine learning, developmental psychology, and robotics.

Research Focus

Key Achievements

26
H-Index
46
Papers
2,997
Total Citations
65
Avg Citations/Paper
🏆 Most Cited Paper
The iCub humanoid robot: An open-systems platform for research in cognitive development
606 citations · 2010
📈 Most Prolific Year: 2017 (7 Papers)
🤝 Key Collaborators: 52
🏛 Institutions: University of Plymouth, École Nationale Supérieure de Techniques Avancées, Instituto Superior Técnico, INESC TEC, Instituto de Engenharia de Sistemas e Computadores Investigação e Desenvolvimento, Institut national de recherche en sciences et technologies du numérique

Top Papers

  1. 1
  2. 2
  3. 3
  4. 4
  5. 5
  6. 6
  7. 7
  8. 8
  9. 9
  10. 10

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago