The is a ‘groundbreaking advancement’ in LiDAR technology, integrating a full multi-channel FMCW LiDAR on a single silicon photonics chip and an integrated FMCW LiDAR System-on-Chip (SoC), which the company claims, ‘sets a new industry benchmark in precision’.
Utilising the industry’s first purpose-built digital LiDAR processor SoC, the iND83301 (“Surya”) developed by indie Semiconductor, the Eyeonic Mini achieves an impressive level of detail, delivering an order of magnitude greater precision than many existing technologies while being one-third the size of last year's model.
This latest innovation builds upon the success of SiLC’s first commercial FMCW LiDAR system, the Eyeonic Vision System, founded on an integrated silicon photonics chip and designed specifically for machine vision applications.
SiLC’s Eyeonic Vision Chip, central to the system, amalgamates all essential photonics functions into a coherent vision sensor that can meet the demands for performance, affordability and low-power consumption. The system’s accuracy is driven by a 4-channel FMCW LiDAR chip, complemented by indie’s innovative Surya SoC, and equips robots with sub-millimeter depth precision from distances exceeding 10 meters.
This level of precision will help to open new doors in automation, particularly in warehouse logistics and AI machine vision applications, according to SiLC.
For instance, AI-driven palletising robots equipped with the Eyeonic Mini can fully view and interact with pallets, optimising package placement and loading onto trucks with efficiency and safety.
“Our FMCW LiDAR platform aims to enable a highly versatile and scalable platform to address the needs of many applications,” said Dr. Mehdi Asghari, CEO of SiLC Technologies. “At CES this year, we’re demonstrating our long-range vision capabilities of over two kilometres. With the Eyeonic Mini we’re showcasing our high precision at shorter distances. Our FMCW LiDAR solutions, at short or long distances, bring superior vision to machines to truly enable the next generation of AI-based automation.”
