Viewing posts categorised under: Neocortex G2R Cell

Fulfilling the Vision of AI-Driven Automation

3D Vision Guidance, Artificial Intelligence, Machine Learning, Neocortex, Neocortex G2R Cell, Random Bin Picking, Robotic Order Fulfillment, Robotics / 30.11.20172 comments

Sarah Mellish of Yaskawa Motoman Robotics explains the role of artificial intelligence for robotic order fulfillment:

“Technical innovations in artificial intelligence and robotics have unlocked massive potential for retailers to automate the handling of diverse Stock Keeping Units (SKUs) in the order fulfillment process with human-like flexibility at high speed….”

View Yaskawa Motoman blog here.

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Neocortex AI links cyber and physical systems for Industry 4.0

Artificial Intelligence, eCommerce, Machine Learning, Neocortex, Neocortex G2R Cell, Robotic Order Fulfillment, Robotics / 26.10.2017

Neocortex artificial intelligence links cyber/digital systems and physical systems of the Industry 4.0 revolution – where software algorithms control machines that are integrated with each other and users.

Neocortex uses a closed loop system, known as cybernetics, to control robots.  This embedded system uses sensor data coupled with physical movement, further integrating the Internet of Things.

In the supply chain, the above smart system provides a highly flexible robot cell that operates at maximum speed – matching the utility of semi-skilled labor.  The Neocortex-based robotic cell (Neocortex G2R Cell) continues to get smarter with time – adjusting to parts, processes, containers, and orders. Thus, its value increases over time and with use (just like an employee), leading to a SaaS (software as a service) delivery model.

Neocortex SaaS also spans cloud-computing servers.

This broadens the scope and significance of patterns discovered and monitored across the cyber-physical barrier, leading to valuable breakthroughs in advanced analytics of big data: supply chain effectiveness, group learning of robots, introduction of SKUs, quality or vendor problems, damage trends, and customer order satisfaction. This both lowers costs and increases sales.

Watch a great overview of Industry 4.0 implications here.

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Warehouse & Logistics Robotics WW Revenue Projected to Grow 64% CAGR

Artificial Intelligence, eCommerce, Machine Learning, Neocortex, Neocortex G2R Cell, Robotics, Robotics Business / 30.05.2017

Research and Markets projects that the global warehouse and logistics robot market revenue will grow from $1.9B in 2016 to $22.4B in 2021, and units from 40,000 to 620,000. Research Analyst Manoj Sahi states, “new robotics technologies that could yield a return on investment (ROI) in less time than it took a few years ago.” Two key areas the report points out are the growth of mobile robot platforms and industrial robot manipulators.

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Neocortex® G2R Cells are Easy to Both Deploy & Re-Deploy

3D Vision Guidance, Artificial Intelligence, Machine Learning, Neocortex, Neocortex G2R Cell, Random Bin Picking, Robot Vision Guidance, Robotics, Robotics Business / 06.03.2017

A Neocortex® G2R (Goods to Robot) Cell is easy to deploy, like a collaborative robot. Yet it is uses an industrial Yaskawa Motoman robot with up to twice the capacity and 150% the speed of a collaborative robot (up to 800 items per hour).

How easy to deploy is the Neocortex G2R Cell? The average time for a Cell to be up and running at a customer site is one day.  See our fun time-lapse video here.  After it is up and running, our team then optimizes the robot and trains your operators. This contrasts with integrating an industrial robot system that may take weeks before being ready to run.  The Cell’s deployment efficiency is comparable a collaborative robot’s average setup time, which is about half a day.

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Universal Robotics Neocortex Shifts Material Handling Flexibility to Software

3D Vision Guidance, Artificial Intelligence, Machine Learning, Neocortex, Neocortex G2R Cell, Random Bin Picking, Robot Vision Guidance, Robotics / 05.08.2014

Check out this video showing Universal Robotics Neocortex – a patented next-generation machine intelligence software platform. It is guiding a robot to pick up a wide range of parts, providing flexible automation.

Traditionally, flexibility consisted of manually reconfiguring mechanical systems and sensors, and manually re-engineering algorithms to accommodate new parts. Neocortex’s machine learning can automatically handle a wide range of changing parts, reducing the need for manual changeovers. In the past, when a new part was introduced, even if the robot could pick up the new part, the robotic work cell would still require changes in fixturing, sensors, machine vision algorithms, and machine control.

In this video, see Neocortex guide the robot to handle various parts. Also shown is a demonstration of the simple training method for those occasional times an operator needs to teach Neocortex something new – a process that takes less than two minutes.

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