Davide Spinello
Papers
15
Total Citations
154
H-Index
5
About
Davide Spinello’s research lies at the intersection of robotics, nonlinear control, and bio-inspired systems, with a strong emphasis on model-free and data-driven approaches. He is best known for pioneering work in animal-robot interaction, where his 2014 study on information flow in animal-robot interactions (68 citations) demonstrated how nonverbal information transmission can be quantified and leveraged to influence social animal behavior—a foundational contribution to ethorobotics. Spinello has made significant advances in control theory, developing real-time reinforcement learning control for uncertain nonlinear systems and model-free force control for cable-driven parallel manipulators used in weight-shift aircraft actuation. His work on snake-like and centipede-inspired robots for confined environment inspection, including planar kinematics and Timoshenko beam modeling, has practical applications in pipeline exploration and nondestructive testing. Spinello also contributed to anomaly detection in noisy sensor data through entropy-based filters, such as the Rényi entropy filter for eddy current sensors. With over 140 citations across his top publications, his research demonstrates a consistent focus on bridging theoretical control frameworks with real-world robotic systems, particularly in uncertain and constrained environments.
Research Focus
Key Achievements
Top Papers
- 1Information Flow in Animal-Robot Interactions68 citations · 2014
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- 3Planar kinematics analysis of a snake-like robot15 citations · 2013
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