Universal Logic’s years as practitioners, implementing state-of-art automation, has given us deep insight into the interplay between invention and utility. We have engaged with a spectrum of clients from technocrats to novices, on a range of industrial applications. Through it all, one thing remains clear. Success in deploying a complex, multi-technology solution – blending vision, AI and motion control, resides in the close interplay and analysis between these disparate engineering domains. As magnificent as robots, sensors and algorithms are individually, it is their combination in service to an application that allows cutting edge automation to handle real-time dynamic variability.
Our full-stack software, Neocortex, is comprised of DeepEye (AI), Autonomy (path planning and obstacle avoidance), and Spatial Vision (middleware). It is machine agnostic. The software provides a closed-loop, behavior-based system of sense/act/learn and represents a profound expansion of manufacturing execution systems (MES) in an area of Industry 4.0 know as IoRT (Internet of Robotics Things). Neocortex is embodied, that is, physically in the world, controlling movement through space, and learning from that action. This is a paradigm shift in the way to think about software. Intelligence emerges because it has a physical form. The software/hardware union and the environment constitute two halves of a complex dynamical system. Neocortex senses the environment and reacts, changing the environment which updates the sensing and behavior. They are a closed loop.
Software structures easily allow for highly layered communications and decision making processes. As exposure to new variables increases over time, a rich set of exception handling protocols develop in Neocortex. The data base of retained and applied learning are brought to bear with every installation. There is a direct corollary between robust behavior and the layers of decision making options the software evaluates in milliseconds before executing an action.
The embodied character of Neocortex is reflected in Universal’s IOT profile, in that we are both a software developer and a system integrator. This is a great strength. Our intimate experience coupling the software and hardware, provides the real-world feedback necessary to perfect the craftmanship of Neocortex. We also team with other integrators, who benefit from our advice and sympathy as fellow integrators.
Our time on the line has given us the humility to know where the state-of-art actually is. Give us a call to discuss your application. We are very generous with our knowledge.Read More >>
If your robots could text you, it’s first message would read: “If I only Had a Brain”
Neocortex Leads the industry with a software “Brain” that gives robots human-like flexibility at high speed.
As Ray Bolger rightly exclaimed in the Wizard of Oz in 1939 “I could think of things I’d never Thunk before, And then I’d sit down and think some more.” Welcome to Industry 4.0 and the world of smart robots. Over the last few years, advances in the coupling of AI, 3D vision, and robot control, have spawned the expansion of machines replacing or working closely with laborers, manifesting all the benefits of automation to new horizons.
Universal spent a decade advancing it’s robot software brain, Neocortex. Today the technology is integrated across the supply chain from handling retail products to manufacturing, allowing our customers to reap the benefits of lower operating cost, improved reliability, and mitigation of risk. The product is achieved 6 Sigma reliability with picking speeds up to 1800 cycles per hour, tripling typical manual output.
Upgrade or Retrofit your current robots to Smart Robots and achieve both increased adaptability and productivity out of your Robots!
Read a fascinating article Dumb Robots vs. Smart Robots “If we want machines to think, we need to teach them to see” Fei-Fei Le, Chief Scientist Google, AI/Machine Learning.
From Bloomberg News: Make Dumb Industrial Robots SmartRead More >>
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….”Read More >>
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.Read More >>
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.Read More >>
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.Read More >>
Frank Tobe’s article in Robohub regarding what’s hot in robotics reads like a who’s who of companies providing state-of-the-art applications in robotics. He breaks down the trends into four buckets, one of which I’d like to address – Advances in Visual Perception.
Here’s what he says:
“Vision-enhanced robotic systems are becoming the top reason for upgrading and deploying vision-enabled robots and a core reason for the steady upward growth of the robotics industry…. Artificial intelligence and various AI learning systems have been improving regarding visual perception, and many new companies (such as Universal Robotics and their Neocortex system) are now either offering vision systems that can supplement existing fixed systems or offering mobile manipulators that can find and determine how best to pick and handle all sorts of objects from plastic-wrapped toys to boxes, cases and skids of materials.”
Frank’s points are correct. Let’s unpack the reasons for this burgeoning market opportunity.Read More >>
Robotic material handling occurs in unstructured environments. In addition, the objects to be moved or manipulated by the robot often have never been seen before, vary constantly, and are in random locations. In the past, there was a tradeoff between throughput and flexibility.
Enjoy this short video blog as I explain on the whiteboard the current status of robotic solutions in the depalletizing application workspace, using throughput and flexibility as the main variables. It represents state of the art, industrial grade solutions for vision-guided robots, advanced vision-guided robots, and machine learning-guided robots.
Enjoy!Read More >>
In a recent article, Boston Consulting Group (BCG) points out that spending on robots worldwide is expected to grow from $15 billion in 2010 to $67 billion in 2025. The $52 billion increase in 15 years is a compounded annual growth rate of 10%. They attribute this growth to a convergence of falling hardware prices, performance improvements, and easier application software combined with increased flexibility and finesse. This results in robots being useful in a much broader set of applications than you might traditionally think of – such as automotive assembly and welding.Read More >>
Clint Reiser points out in the linked article that a new revolution in supply chain analytics is occurring. There is new level of data detail, it’s coming at us faster, providing bigger patterns and better insights.
The detail isn’t just point-of-sale information, customer buying patterns, or fleet telematics. From Universal’s perspective, the combining of machine learning and machine vision into robust automated solutions for material handling processes previously thought as random is a unique source of this data.Read More >>