Eye and Robot: When machines learn to see
Our vision, a complex biological marvel, is now inspiring the world's leading robotics laboratories. By attempting to replicate the performance of the human eye, engineers, neuroscientists, and industrialists have given birth to a new discipline at the intersection of optics, artificial intelligence, and biomechanics: computer vision. What are the links between the biological eye and its robotic counterpart, the already real applications of this technology in our lives, and the promises it holds for tomorrow? We discuss them in this new report.
Understanding Computer Vision: From the Biological Eye to the Algorithm
The first artificial vision systems were directly inspired by human physiology, using sensors that mimic the retina, image processing modeled on the brain's visual areas, and convolutional neural network learning. The human eye, with its 126 million photoreceptors and its ability to simultaneously analyze shape, color, movement, and depth, remains an unrivaled benchmark.
But the machine also has its advantages: it can "see" invisible spectra (infrared, ultraviolet), support higher processing speeds, and even analyze images 24 hours a day without the slightest fatigue.
In industrial robots, smart cameras already enable inspection, detection, and decision-making using visual recognition algorithms. At Boston Dynamics , a robotics company, quadruped robots analyze their environment in real time to adjust their movements. In autonomous cars, however, vision enables the detection of pedestrians, signs, and obstacles.
By copying the visual mechanisms of living things, artificial vision technologies show that machine intelligence often relies on a better understanding… of biological intelligence.
Artificial vision: a short technical glossary
Computer vision : a set of technologies that allow machines to interpret images.
Machine learning : Algorithms learn to recognize objects from examples.
Deep learning : more complex learning, based on artificial neural networks close to the functioning of the human brain.
Smart cameras : autonomous systems incorporating sensor, image processing and algorithms in a single housing.
Embedded AI : artificial intelligence integrated directly into the device (without using a cloud).
The Eye and the Robot: When robotics is inspired by living things: the Biomimetic Revolution
Biomimicry is one of the major trends in robotic vision. In Zurich, the ETH (Swiss Federal Institute of Technology) is developing artificial retinas inspired by flies, capable of capturing ultrafast movements. Other researchers have recreated panoramic visual systems similar to those of dragonflies, offering a 360° field of vision.
The EC-Eye artificial retina, created by Hong Kong researchers in 2020, goes further: it reproduces the curvature and photoreceptor structure of the human eye with impressive precision, using nanosensors integrated into an aluminum dome. The goal? To eventually offer vision comparable to our own, but implantable, adaptable, and connected to electronic devices.
The "seeing" robot iCub , developed by the Italian Institute of Technology, learns to explore its environment like a human baby: it looks, imitates, and adjusts. Its vision, combined with motor learning, allows for more natural interactions with objects and humans.
This return to the model of the living, far from being a simple mimicry, suggests that nature remains one step ahead in the art of reconciling performance, adaptability and energy saving.
Zoom culture – Robot eyes in cinema
From the red gaze of HAL 9000 (2001: A Space Odyssey) to the Terminator's "thermal sight," science fiction has long fantasized about how machines see the world. More recently, the robot Wall-E offered a touching and expressive gaze, without ever speaking. These depictions—sometimes prophetic—fuel the imaginations of engineers today.
Concrete applications: from industry to medicine and disability assistance
In production lines, machine vision is gradually replacing human inspections. It can detect defects invisible to the naked eye, guide robotic arms with precision, and measure distances in three dimensions.
In medicine, vision systems are used for surgical imaging, assisted robotics (such as the Da Vinci Surgical System ) or even for automated diagnosis in ophthalmology (such as the detection of diabetic retinopathy via AI).
But one of the most promising aspects of this technology is its application in assisting the visually impaired. Devices like OrCam MyEye or Envision Glasses incorporate a smart camera mounted on glasses to describe aloud what the user would "see": text, faces, colors, objects.
These devices, while expensive, pave the way for a new form of "assisted vision," in which the machine becomes a perceptual interface for impaired eyes. The rise of artificial vision in such diverse fields underscores the extent to which "seeing" is no longer just a biological sense, but also a lever for social, economic, and medical innovation.
Innovation Portrait – Prophesee, the French start-up reinventing the retina
Founded in Paris, Prophesee has developed a neuromorphic camera inspired by the human eye. It doesn't capture images continuously, but only when a pixel detects a change. The result: real-time, ultra-responsive, and energy-efficient vision, already used in automotive and surveillance systems.
Towards a symbiosis between human and machine vision?
Machine vision doesn't necessarily seek to replace human vision, but to extend it, enrich it, or make it accessible in new ways. By drawing inspiration from biology to create machine eyes, researchers are pushing the boundaries of perception. More than a technical feat, the fusion of human and robotic vision questions our relationship to perception and the delegation of gaze, in a world where machines could soon… see for us.
But this technology also raises questions: ethical, economic, and security. Who owns the visual data captured by intelligent machines? How far can we go in implanting devices into the human body? And what limits is our society willing to cross to "see" better?
The convergence between human and robotic vision seems inevitable. It opens up as many opportunities as it does debates, and as is often the case, what we do with this new "view" will depend above all… on our collective perspective.
