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Opteran to bring natural intelligence to SAFELOG mobile robots

By The Robot Report Staff | March 22, 2024

SAFELOG's mobile robots can operate in a range of warehouse and factory settings. | Source: SAFELOG.

SAFELOG’s mobile robots can operate in a range of warehouse and factory settings using Opteran Mind. | Source: SAFELOG

Opteran Technologies this week announced at LogiMAT a partnership with SAFELOG GmbH, a manufacturer of order-picking and transportation robots for warehouses and factories. SAFELOG will integrate its mobile robots with Opteran Mind, a general-purpose autonomy product.

“We are delighted to announce our partnership with SAFELOG, as this is another significant milestone on our path to commercializing Opteran Mind,” stated David Rajan, co-founder and CEO of Opteran Technologies.

“We are seeing a rapid take up of our technology across the U.S., Japan, and Europe, so today’s agreement with SAFELOG underlines why our technology is best in class for localization and mapping for mobile robots,” he added. “It also shows that while ‘natural intelligence’ is unique in the market, our inputs and outputs are standard, making Opteran Mind a simple and attractive solution to integrate with existing mobile robots.”

The companies said the multi-year agreement will enable SAFELOG to address the urgent need for greater productivity from autonomous mobile robots (AMRs) operating in hazardous and dusty environments. Opteran claimed that its technology can enable AMRs to handle dynamic lighting and ever-changing obstacles without GPS.


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SAFELOG aims to reduce failure rates

Markt Schwaben, Germany-based SAFELOG said it is developing a new generation of mobile robots that combine robustness and efficiency. A key objective of its project with Opteran is to reduce robot failure rates because of localization errors with existing 2D and 3D lidar, as well as with visual simultaneous localization and mapping (vSLAM).

Another challenge to productivity is when hundreds of automated guided vehicles (AGVs) operate together in a warehouse setting because each installation requires an infrastructure consisting of magnetic tracks and QR code reflectors. This can increase commissioning time and operating costs.

Opteran said its localization software enables new projects to be activated quickly and efficiently without additional infrastructure. 

“There are a lot of challenges for existing autonomy solutions to overcome in the complex conditions of a warehouse, so we have been amazed by what Opteran Mind can achieve,” said Michael Reicheicher, managing director of SAFELOG, in a release. “Opteran’s technology performs significantly better in our mobile robots, which will be hugely beneficial for our customers. Natural Intelligence, their approach to AI, offers a robust technology that we are confident will differentiate our AMRs in the global market.”

Opteran Mind promises navigation breakthrough

Opteran Mind is based on 10 years of research into insect brains. The company, which has facilities in London and Sheffield in the U.K. and Boston in the U.S., said it reverse-engineered natural brain algorithms. 

“Fundamentally, nature does navigation more efficiently than robots,” said Opteran Technologies. By replicating nature’s approach in a model that the company calls “natural intelligence,” it said it has delivered a “dramatic breakthrough.”

Opteran estimated that its system could cost less than $160 running on a Sony and ARM Core and using Sony IMX219 cameras and RK4566 ARM chips. In comparison, current systems can range in cost from $8,400 for a 2D lidar setup to $27,000 for a 3D lidar setup, it said.

Opteran and SAFELOG demonstrated their collaboration at LogiMAT in Stuttgart, Germany. They showed a SAFELOG mobile robot using Opteran Mind, which they said could increase adaptability and minimize downtime.

The partners said Opteran Mind can be embedded in ground-based robots and aerial drones for a wide variety of applications, from logistics and warehouse distribution to oil and gas inspection, mining, and autonomous vehicles.

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