AI Improves Maching Vision Resolution

| Information and Communication Technology

The Eyeonic Mini is targeted at machine vision applications that require short-range vision detection

SoC LiDAR technology is aiding the next step in AI enabled machine vision with sub-millimeter resolution

SiLC Technologies has launched the Eyeonic Vision System Mini (Eyeonic Mini) with advanced LiDAR technology. The system has a full multi-channel FMCW LiDAR on a single silicon photonics chip and an integrated FMCW LiDAR System-on-Chip (SoC) bringing significant improvements in precision detection.

Eyeonic Mini makes use of a purpose-built digital LiDAR processor SoC, the iND83301 (Surya), which was developed by indie Semiconductor. This processor enables the Eyeonic Mini to achieve unprecedented levels of detail, delivering an order of magnitude greater precision than existing technologies while being one-third the size of the company’s previous model. The latest innovation builds on 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, delivering a compact product that meets the demands for performance, affordability and low-power consumption. The system’s high 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 opens new doors in automation, particularly in warehouse logistics and AI machine vision applications. 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. For large logistics orgnisations in Europe and the USA, this technology promises to make a significant different to warehouse operations and the broader logistics industry, significantly boosting efficiency in loading and unloading processes.

More intelligence for robotics

Robot specialist, Dexterity is working on incorporating SiLC technology into its robot autonomy platform. The company is focused on AI, machine learning and robotic intelligence to make warehouses more productive, efficient and safe, with CEO Samir Menon having chosen to to partner with SiLC to unlock LiDAR for the robotics and logistics markets.

“The company’s technology has a considerable effect on depth sensing and will enable easier and faster adoption of warehouse automation and robotic truck load and unload operations,” he says.

When the improved depth sensing of the LiDAR technology is combined with the AI software used for robot intelligence, new levels of machine vision resolution and precision of operations become achievable.

Precision for complex applications

For machines to be capable of truly improving the technology of logistics and other complex operations, their vision equipment must be powerful, compact, scalable and unaffected by complex, unpredictable environments and conditions, including interference from other systems.

The equipment must provide the right combination of motion, velocity, polarisation and precision, the combination of which present too complex a challenge for existing time-of-flight-based vision systems and instead point to FMCW as the required platform. FMCW technology enables a new generation of imaging systems that can directly capture images for AI machine vision, factory robots, home security, autonomous vehicles and perimeter security applications.

According to Dr Mehdi Asghari, CEO of SiLC Technologies, the FMCW LiDAR platform aims to enable a highly versatile and scalable platform to address the needs of many applications.

“Our FMCW LiDAR products, at short or long distances, bring superior vision to machines to truly enable the next generation of AI-based automation,” he says.

Jonathan Newell
Latest posts by Jonathan Newell (see all)

Related news

Read More News From Unspecified Company: