A team of researchers from the engineering and applied science school at the University of Virginia has developed An innovative biomimetic vision system Inspired by the unique visual capacities of the prayer mantis eyes. This innovation aims to improve the performance of various technologies, including autonomous cars, drones and robotic mounting lines while taking an important challenge in AI -oriented systems: the inability to perceive static or slow objects in 3D space.
For example, autonomous cars are currently based on visual systems which, as well as the eyes composed of most insects, excellent in monitoring movement and offer a large field of vision but fight with the perception of depth. However, the prayer mantis stands out as an exception. His eyes, which overlap in their field of vision, give it a binocular vision – allowing it to perceive depth in 3D space, a critical capacity that the research team sought to reproduce.
The researchers, led by PH.D. The candidate byungjoon Bae, designed artificial compound eyes which imitate this biological capacity. These “eyes” incorporate microlean and several photododids using flexible semiconductor materials that imitate convex shapes and faceted positions found in the mante's eyes. This design allows a large field of vision while maintaining an exceptional perception of depth.
According to BAE, their system provides real -time spatial consciousness, which is crucial for applications that interact with dynamic environments. One of the main innovations in this system is its use of on -board computer science – data processing directly in or near the sensors that capture it. This approach considerably reduces data processing deadlines and energy consumption, achieving more than 400 times energy consumption compared to traditional visual systems. This makes technology particularly well suited to low -power vehicles, drones, robotic systems and intelligent household appliances.
The team's work shows how these artificial compound eyes can constantly monitor changes in a scene by identifying and coding the pixels that have changed. This method reflects the way insects treats visual information, using the movement parallax to differentiate close and distant objects and perceive movement and spatial data.
By combining advanced materials, innovative algorithms and an in -depth understanding of biological vision systems, researchers have created a computer vision system that could revolutionize AI applications. This biomimetic approach improves not only the accuracy and efficiency of visual treatment, but also opens up new possibilities for the future of AI -focused technologies.
While autonomous cars, drones and other AI systems continue to evolve, the integration of these biomimetic vision systems could mark a major jump forward, which makes these technologies safer and more reliable in real environments.
