-warehouse-robotics-solutions-

Vision systems are driven by machine learning technologies.  

Robots are highly collaborative. Amazon's Kiva robots, for example, are designed to be operated in a section of the warehouse off limits to humans.  Vecna's robots have vision systems that allow them to navigate safely around humans and share common transit paths...

Their robots can also collaborate with other robots.  For example, a case pick robot might place a case on an AGV style robot that would then transport the case to a pallet build station.

Vision systems are driven by machine learning technologies.  At Vecna their robots come with "remote assist" capabilities. When it comes to training a vision system how to recognize and react to its environment, robots in warehouses are apt to discover things they have never seen and don't know how to react to.  In this instance, the robot can ask for help and a human can remotely provide supervision. This feature, they argue, also allows the robot to learn from its environment more quickly.  https://www.forbes.com/

The final differentiator that I found to be interesting, is that they are "platform agnostic."  In other words, they can put their robot brain into a forklift or tugger offered by another vendor and turn it into a robot.

Mr. Theobald made the point that to solve a material handling problem, it is not always clear which robot or combination of robots and humans are best suited to solve the problem.

 They offer simulation services - both discrete event simulation a physics simulation engine that makes sure the robot mechanisms are fully reacting to the laws of physics - to discover the solution with the best ROI. Historical data from a customer site can be fed into the simulation to improve the fidelity of the results.

Licklider became interested in information technology early in his career. His ideas foretold of graphical computing, point-and-click interfaces, digital libraries, e-commerce, online banking, and software that would exist on a network and migrate wherever it was needed. Much like Vannevar Bush's, Licklider's contribution to the development of the Internet consists of ideas, not inventions. He foresaw the need for networked computers with easy user interfaces.

Licklider was instrumental in conceiving, funding and managing the research that led to modern personal computers and the Internet. In 1960 his seminal paper on "Man-Computer Symbiosis"  foreshadowed interactive computing, and he went on to fund early efforts in time-sharing and application development, most notably the work of Douglas Engelbart, who founded the Augmentation Research Center at Stanford Research Institute and created the famous On-Line System where the computer mouse was invented.

He also did some seminal early work for the Council on Library Resources, imagining what libraries of the future might look like,  which he had described as "thinking centers" in his 1960 paper

"thinking centers" 

digital libraries

"Man-Computer Symbiosis"

machines with the ability to display intelligence similar to human

in the next 40 years, robots are going to take your job.

I don’t care what your job is. If you dig ditches, a robot will dig them better. If you’re a magazine writer, a robot will write your articles better. If you’re a doctor, IBM’s Watson will no longer “assist” you in finding the right diagnosis from its database of millions of case studies and journal articles. It will just be a better doctor than you.

In "Man-Computer Symbiosis", Licklider outlined the need for simpler interaction between computers and computer users.  Licklider has been credited as an early pioneer of cybernetics and artificial intelligence (AI),  but unlike many AI practitioners, Licklider never felt that men would be replaced by computer-based beings. As he wrote in that article: "Men will set the goals, formulate the hypotheses, determine the criteria, and perform the evaluations. Computing machines will do the routinizable work that must be done to prepare the way for insights and decisions in technical and scientific thinking".  This approach, focusing on effective use of information technology in augmenting human intelligence, is sometimes called Intelligence amplification (IA).

Since its inception in 1956, artificial intelligence is known as the intelligence that the machines and software show, which simulates human intellectual ...