Papers
21
Total Citations
318
H-Index
12
About
Matteo De Carlo is a pioneering researcher in evolutionary robotics, with a particular focus on the co-evolution of robot morphologies and controllers in real-world physical systems. His most celebrated contribution, "Real-World Evolution of Robot Morphologies: A Proof of Concept" (2017, 58 citations), helped establish the feasibility of robots that can literally reproduce and evolve their body plans using physical hardware — a landmark achievement in the field. Through his central involvement in the **Autonomous Robot Evolution (ARE)** project, De Carlo has tackled some of the discipline's most formidable challenges: designing automated fabrication systems, bridging the simulation-to-reality gap, and developing efficient learning algorithms such as CMA-ES and Bayesian Optimisation to help "newborn" robots rapidly adapt inherited controllers to novel morphologies. His work on combining evolution with learning frameworks has generated substantial community interest, with multiple papers accumulating 17–26 citations each. Collectively, his research advances a compelling long-term vision — autonomous robotic ecosystems capable of self-directed adaptation over extended periods without human oversight — making him an influential voice shaping the future of embodied artificial intelligence.
Research Focus
Key Achievements
Top Papers
- 1Real-World Evolution of Robot Morphologies: A Proof of Concept58 citations · 2017
- 2Learning directed locomotion in modular robots with evolvable morphologies26 citations · 2021
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- 10Hardware Design for Autonomous Robot Evolution17 citations · 2020