Agostino Gibaldi
Papers
7
Total Citations
85
H-Index
6
About
Agostino Gibaldi is a leading researcher in bio-inspired robotics and active vision, with a focus on how biological principles can be applied to robotic perception and control. His work centers on developing neuromorphic models for binocular coordination, particularly vergence eye movements—the ability to align both eyes (or cameras) on a single point in space. Gibaldi’s major contributions include creating distributed neural representations of binocular disparity that allow robotic systems to autonomously learn and control vergence without explicit disparity computation. His 2014 paper on a hierarchical system for peripersonal space representation (26 citations) is his most cited, demonstrating how robots can reach targets in unstructured environments. Other influential works include real-time vergence control on the iCub humanoid robot (14 citations) and autonomous learning of disparity-vergence behavior through population reward (8 citations). Gibaldi’s research bridges computational neuroscience and robotics, offering elegant solutions for depth perception and spatial interaction. His portable bio-inspired architecture for efficient vergence control (2016, 10 citations) highlights his commitment to practical, deployable systems. For students and researchers, Gibaldi’s work exemplifies how understanding neural mechanisms can lead to more adaptive, human-like robotic vision.
Research Focus
Key Achievements
Top Papers
- 1
- 2LEARNING EYE VERGENCE CONTROL FROM A DISTRIBUTED DISPARITY REPRESENTATION15 citations · 2010
- 3
- 4A Portable Bio-Inspired Architecture for Efficient Robotic Vergence Control10 citations · 2016
- 5
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- 7Vector Disparity Sensor with Vergence Control for Active Vision Systems6 citations · 2012