Matthieu Dujany

École Polytechnique Fédérale de Lausanne

Papers

1

Total Citations

2

H-Index

1

About

Matthieu Dujany is a researcher at the forefront of bio-inspired robotics and adaptive locomotion, with a core focus on how robots can autonomously generate and recover gaits in response to morphological changes. His most cited work, "Emergent adaptive gait generation through Hebbian sensor-motor maps by morphological probing" (2020), tackles a fundamental challenge in robotics: the gap between animals' ability to adapt locomotion "on-the-fly" after injury and the brittleness of traditional controllers. Dujany's key contribution lies in extending Hebbian learning principles to create sensor-motor maps that enable robots to probe their own morphology and self-organize new gaits without explicit programming. While his citation count is modest—reflecting the nascent stage of this research—the conceptual impact is significant, positioning his work as a foundational step toward truly resilient, autonomous systems. This research has implications for disaster response, prosthetics, and field robotics, where adaptability to damage is critical. Dujany's approach represents a paradigm shift from pre-programmed control to emergent, embodied intelligence, making him a promising voice in the quest for robots that can learn to walk, and re-walk, like living creatures.

Research Focus

Key Achievements

1
H-Index
1
Papers
2
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
Emergent adaptive gait generation through Hebbian sensor-motor maps by morphological probing
2 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: École Polytechnique Fédérale de Lausanne

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago