Geek+ and Intel launch Vision Only Robot Solution for smart logistics

Geekplus Technology Co. today launched its Vision Only Robot Solution. The system includes Intel Visual Navigation Modules, which Geek+ said will drive the digital transformation of the logistics industry. 

“The Vision Only Robot Solution, developed in collaboration with Intel, effectively leverages the depth vision perception of the Intel RealSense camera,” stated Solomon Lee, vice president of product at Geek+. “Together with the deep algorithmic innovations from both sides, it results in a boost in business growth and efficiency for customers, driving the digital and intelligent upgrade of smart logistics.”

Geek+ claimed that its new system is the world’s first vison-only autonomous mobile robot (AMR) using Intel Corp.‘s Visual Navigation Modules. It also features algorithmic innovations in V-SLAM (visual simultaneous localization and mapping) positioning, composite detection networks, and robot following, the partners said. This allows for highly accurate navigation and obstacle avoidance, helping enterprises cope with diverse and complex logistics scenarios while enhancing both efficiency and accuracy, said Geek+.

The vision-only robots equipped with the Intel Visual Navigation Modules will debut this week at CeMAT in Shanghai. Geek+ said it plans to strengthen its partnership with Intel to develop more smart logistics systems.

Founded in 2015, Geek+ said that more than 1,000 customers use its AMRs for warehouses and supply chain management. The company has offices in the U.S., Germany, the U.K., Japan, South Korea, China, and Singapore. It opened a 40,000-sq.-ft. facility near Atlanta and partnered with Floatic last month.

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Intel RealSense supports vision-based AI

Geek+ explained that its Vision Only Robot Solution integrates the Intel RealSense camera. This camera has an all-in-one design that enables all depth calculations to be performed directly within the device. This will result in low power consumption and independence from specific platforms or hardware, said the companies.

The Intel RealSense also supports various vision-based AI, noted Intel. When paired with a dedicated visual processor, it can accelerate the machine-learning process and shorten the deployment cycle for new automation.

Thanks to the Intel RealSense camera, Geek+ said its Vision Only Robot can observe, understand, and learn from its environment. By obtaining highly accurate and consistent depth data, the robot can accurately recognize and interact with its surroundings, the company said.

“Highly accurate and consistent depth vision data is critical for [an] AMR to achieve environmental perception, significantly influencing its performance in positioning, navigation, and obstacle avoidance,” said Mark Yahiro, vice president of corporate strategy and ventures and the general manager of the RealSense business unit within Intel’s Corporate Strategy Office.

“Through collaboration with Geek+, we are driving AMR innovations based on depth vision data, enabling logistics robots to deliver highly stable and accurate transport services in complex environments, thereby empowering agile, digital, and intelligent supply chains,” he said.

In addition to the camera, the Intel Visual Navigation Module includes the Robotic Vision Hub, which contains components such as the Intel Core i7-1270P processor and connection modules. The module also enables cloud-edge collaboration through high-speed networks, said the partners.

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Geek+ aims for algorithmic innovation 

Geek+ said is building on the Intel Visual Navigation Module to provide reliable computational support for algorithms running on its Vision Only Robot:

• V-SLAM positioning algorithm: This fuses multi-sensor data and various visual feature elements to generate composite maps, such as point feature maps, line feature maps, object maps, and special area maps. It can deliver reliable and precise positioning in complex and dynamic environments, said the companies.
• Composite detection network: With both a traditional object-detection network and a validation network, it processes detection data from multiple dimensions, thus enhancing accuracy and reducing the false detection rate.
• Robot following: By integrating modules such as personnel detection, re-identification, and visual target tracking, Geek+ said it has developed a flexible and efficient visual perception pipeline. Once the relative position between the target personnel and the AMR is determined, the local planning algorithm in Geek+’s self-developed RoboGo, a robotic standalone system, will enable autonomous obstacle avoidance for smooth AMR following of target personnel.

Geek+ said the combination of the Intel Visual Navigation Module’s depth perception and collaborative algorithmic innovations will ensure efficiency for its Vision Only Robot. It will also provide high precision and efficiency for environmental perception, positioning, and tracking, the company said.

Intel and Geek+ said they expect to see widespread adoption of these robots in areas such as factory and warehouse transportation.