The Eyeonic Vision Sensor has demonstrated the ability to perceive, identify, and avoid objects at a range of more than 1 kilometer. Having previously demonstrated a detection range of more than 500 m at CES earlier this year, SiLC has now optimized its technology to go beyond 1,000 m–a feat that no other company can claim. Ultra-long-range visibility is a requirement in many industries that utilize machine vision, including automotive, metrology, construction, drones, and more. Specific scenarios include providing enough time for a vehicle to evade an obstacle at 
highway speeds; enabling a drone to avoid others in the sky; and controlling deforestation by making precision mapping and surveying of forests possible.
Next-gen vision sensors that incorporate millimeter-level accuracy, depth and instantaneous velocity are key to true autonomous driving and other machine vision applications–and FMCW LiDAR is the optimal technology to make this a reality. First announced in December of 2021, SiLC’s Eyeonic Vision Sensor is a first-of-its-kind FMCW LiDAR transceiver. The heart of the Eyeonic Vision Sensor is SiLC’s silicon photonic chip which integrates FMCW LiDAR functionality into a single, tiny chip. Representing decades of silicon photonics innovation, this chip is the only readily-integratable solution for manufacturers building the next generation of autonomous vehicles, security solutions and industrial robots.
“Our technology platform is flexible enough to address ultra-long-range to ultra-short-range applications which speaks to our understanding of what is needed to truly make machine vision as good or better than human vision,” said Dr. Mehdi Asghari, SiLC’s CEO and founder. “The highly detailed, accurate instantaneous velocity and ultra-long-range information that our Eyeonic Vision Sensor provides is the key to helping robots classify and predict their environment–in the same way that the human eye and brain process together.”
SiLC Technologies, 181 W Huntington Dr., Ste 200, Monrovia, CA 91016, www.silc.com/
