• Animal Eyes
• Artificial Vision
• Bioinspiration
• Computer Vision
• Image Formation Simulation
• Optics
• Social Robots

Bioinspired Articial Vision is a multi-disciplinary research eld aimed at developing technology and system implementing visual functions taking inspiration from studies on biological vision apparatus able to accomplish the same function. Such a type of articial systems include a visual body and a visual brain. The body is dened as the whole of the robotic eyes optical and imaging components, and their associated optical and imaging early (low-level)processing, and the brain is the whole cognitive (high-level) visual processing. This PhD thesis targets three foundational innovations in all the phases of articial vision system design. First, a bioinspired technology to accomplish a low-level visual mechanism such as keep objects in focus. It consists in the design, development and characterization of a tunable lenses entirely made of soft solid matter (elastomers) whose working principle is inspired by the accommodation in bird and reptile. Second, a visual perception system which implement the high-level visual tasks (e.g. estimation of visually salient stimuli, face/gesture detection and recognition, etc.) that a humanoid robot need to extract during the social interaction with humans. Third and last innovation target a evolutionary-driven methodology in design the over-all articial vision system. State-of-the-art evolutionary algorithms have been used only in developing the visual brain through simulation. Here, I introduce a software tool that enable a realistic estimation of the visual body imaging response that can be used to model this part of the system in a simulated scenario