The Chart of the Week is a weekly Visual Capitalist feature on Fridays. Industrial robots have come a long way since George Devol invented "Unimate" in 1961. After pitching his idea to Joseph Engelberger at a cocktail party, the two soon saw their new creation become the first mass-produced robotic arm to be used in factory automation. Today, this robot class is raising the bar of global manufacturing to new heights, striking a seamless mix of strength, speed, and precision. As a result, demand for industrial robots keeps growing at a robust 14% per year, setting the stage for 3.1 million industrial robots in operation globally by 2020.
In terms of sheer speed and precision, delta robots are some of the most impressive to watch. They're also some of the most useful, for the same reasons--you can see them doing pick-and-place tasks in factories of all kinds, far faster than humans can. The delta robots that we're familiar with are mostly designed as human-replacement devices, but as it turns out, scaling them down makes them even more impressive. In Robert Wood's Microrobotics Lab at Harvard, researcher Hayley McClintock has designed one of the tiniest delta robots ever. Called milliDelta, it may be small, but it's one of the fastest moving and most precise robots we've ever seen.
Developing a robust, flexible, closed-loop walking algorithm for a humanoid robot is a challenging task due to the complex dynamics of the general biped walk. Common analytical approaches to biped walk use simplified models of the physical reality. Such approaches are partially successful as they lead to failures of the robot walk in terms of unavoidable falls. Instead of further refining the analytical models, in this work we investigate the use of human corrective demonstrations, as we realize that a human can visually detect when the robot may be falling. We contribute a two-phase biped walk learning approach, which we experiment on the Aldebaran NAO humanoid robot.
The creators of Mimus, a 1,200-kg (2646 lbs.) industrial robot that can sense and respond to human movement, believe it's possible. Part art-installation, part display of engineering ingenuity, Mimus was created from an ABB IRB 6700 robot and commissioned for the "Fear and Love" exhibit at The Design Museum with the goal of promoting companionship between humans and machines. The robot's creator notes that this particular machine is more like a "she" than an "it." Most industrial robots are made to perform repetitive tasks, but Mimus has no pre-planned movements and is instead programmed to freely explore the space around her and to interact with visitors. The exhibit designers wanted to replicate the experience of seeing a large, exotic animal at a zoo.
Manufacturing sites worldwide use industrial robots to streamline and automate operations. Japan has led the world in industrial robot technology, and now is about to spur an even greater evolution by combining this technology with an open source deep learning framework developed in Japan. Deep learning enables industrial robots to make judgments in complex operational situations by learning from past examples. Moreover, the learning can be shared between robots to increase efficiency. Watch this video to learn how this innovative approach will deliver previously unavailable levels of advanced automation in manufacturing.