Papers
15
Total Citations
357
H-Index
10
About
Nino Cauli is a leading researcher at the intersection of neurorobotics, biologically inspired control, and autonomous service robotics. His work is distinguished by pioneering efforts to bridge computational neuroscience and real-world robotic systems, most notably through the development of the Neurorobotics Platform—a comprehensive simulation framework that connects spiking neural network models of the brain to physical robots. This landmark contribution, which has garnered over 117 citations, enables researchers to validate brain models within rich, dynamic sensory environments, advancing our understanding of neural computation and its application to artificial systems. Cauli has also made significant strides in domestic service robotics, authoring a highly cited comprehensive review on control strategies for cleaning robots (74 citations). He has advanced the field through innovative learning-from-demonstration approaches using deep neural networks, enabling humanoid robots like the iCub to autonomously perform complex table-cleaning tasks. His work on head stabilization and adaptive visual pursuit models further demonstrates his commitment to creating more stable, perceptive, and biologically plausible robot controllers. With a portfolio of highly cited publications spanning neurorobotic toolkits, domain-specific languages for neuronal network integration, and autonomous task learning, Cauli stands as a key figure shaping the future of intelligent, adaptive, and brain-inspired robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5Head stabilization in a humanoid robot: models and implementations20 citations · 2016
- 6
- 7A Framework for Coupled Simulations of Robots and Spiking Neuronal Networks17 citations · 2016
- 8
- 9Head stabilization based on a feedback error learning in a humanoid robot11 citations · 2012
- 10