Industrial robots began life as hefty mechanical arms that could spot-weld cars faster than human workers. But today’s versions offer a delicate touch, along with the intelligence to handle more challenging tasks.
In our new edition, we focus on service robots that assist workers on the factory floor. We also discover sensitive robots able to feel pain, a new means of self-protection. And we talk about cognition—the ultimate goal of robotics, according to some experts.
EMO Hannover Video Coverage
For this year’s edition of EMO Hannover, the focus is on smart manufacturing.
We also talk about KUKA’s robots that are taught instead of programmed. And we look into the future with predictive maintenance.
Working is Easy
In tomorrow’s factory, new devices and cobots will decrease the strenuousness of tasks while highlighting worker expertise. Watch our full video report.
Rather than simply taking jobs on production lines, the new generation of service robots is finding its place alongside humans, boosting both productivity and safety.
Industrial robots began life as hefty mechanical arms that could spot-weld cars faster than human workers. But today’s robots have developed a delicate...
Better safety systems and easier programming are making robots practical for an increasing number of manufacturers. For some experts, achieving cognition is the ultimate goal of the fourth robotics revolution.
Features are hard-coded and intelligence is programmed by experts. Therefore, cognition becomes more and more important—especially when it comes to robots learning autonomously to deal with new workpieces or unforeseen situations.
Picking and Grasping
Binpicking / Courtesy of Fraunhofer
Caged automation, followed by cobots and mobile robots, are often considered the first three stages of the robotic revolution, with artificial intelligence (AI) as the fourth. Kraus suggests we are on the way to achieving this.
Object detection for grasping unknown objects benefits from AI. Dex-Net 2.0 includes a synthetic dataset of 6.7 million-point clouds for training of neural networks.
Dex-Net 2.0 is designed for learning Grasp Quality Convolutional Neural Network models that use point clouds to predict the probability of success of candidate object grasps.
Other pioneering steps in the field include sensor systems to tackle transporting workpieces and handling undefined tolerances.
An example of this is their bin-picking solution, bp3™, which has been designed to allow robots to grasp randomly stored objects. This software is capable of locating workpieces in a crate for robotic picking. It uses specially developed algorithms based on a CAD model, and can handle almost any shape of workpiece.
Operators can teach robots about different workpieces and new bins or crates with just a few clicks, and even define complex gripper geometries with an unlimited number of axes.
Highly automated production line / Courtesy of Banner
Nigel Smith, CEO of UK-based TM Robotics, which installs robots around the world, agrees that the repetitive nature of bin-picking makes it ideal for automation. Despite a barrage of media coverage declaring the start of the fourth industrial revolution, industry has struggled with transferring this simple task from human to machine.
The automation of manufacturing processes is a complex issue without a one-size-fits-all solution. There are still arguments as to whether robotics and automation can really outperform human employees.
All bin-picking applications require a 3D camera, vision software and a robotic arm. But now we are seeing the introduction of even more advanced vision systems.
Toshiba Machine’s TSVision3D, for example, does not require CAD data for bin-picking applications. Instead, the system uses a high-speed camera taking 30 frames per second of real-time 3D images. Using this data, the system can identify the best way to handle non-uniform items, regardless of whether the items have a CAD structure available.
Concerns about a future with cognitive robots has led some to call for regulations, while others are focused on the more immediate potential loss of jobs.
One of the most prevalent arguments surrounding industrial automation is the threat it poses to human workers on the factory floor. According to the Annual Manufacturing Report, 83% of companies have implemented some form of automation into their production process in the past five years. But this does not necessarily mean tech has replaced human workers.
Industrial automation is implemented to manage menial tasks on the production line—those that do not require human intelligence. Human workers are thus freed up to concentrate on more complicated tasks, thus improving efficiency and productivity in the facility.
The Age of Cobotics
Jean-Claude Waeldin, project manager at Gebo Cermex (Sidel Group), a global provider of packaging equipment, says “the age of cobotics is taking hold,” but that humans should not feel threatened.
“The age of cobotics is taking hold.”
These developments can improve working conditions while also increasing human productivity by allowing workers to be assigned to higher value-added tasks.
Indeed, Waeldin thinks a combination of machine and human intelligence lies at the heart of smart factory solutions.
The Smart Factory leverages digital technologies to improve performance. This includes assisting operators working on repetitive tasks to increase operations reliability over time, and to allow human intelligence to be used for tasks that can keep line performance as high as possible.
Waeldin concluded: “The use of advanced technologies has already begun to change the image of industry, with factory-based jobs being much more attractive than a few years ago, a trend that is set to increase as Industry 4.0 and the opportunities it presents for automation gathers momentum.”
For this year’s edition of EMO Hannover, the focus is on smart manufacturing with the EOS funny octopus made in one part. We also talk about KUKA’s robots that are taught instead of programmed. And we look into the future with predictive maintenance.
Next generation robots push the boundaries of innovative automation.
Most of us think of robots as stiffly-moving hard, metal machines bristling with wires and cables. While such devices already improve our everyday lives in numerous ways, their rigidity and lack of “sensitivity” to their surroundings often constrains usefulness.
Driven by a burgeoning demand for lighter, cheaper robots that can handle more complex situations and collaborate directly with humans, pioneering bioinspired designs and soft materials are challenging our notion of what robots should look like, and what they can do.
Johannes Kuehn and Sami Haddadin from Hannover’s Leibniz University are currently working on an artificial nervous system which could be used to make robots experience “painful” sensations. The pair equipped a lightweight robotic arm with a tactile fingertip that measures pressure distribution and temperature to mimic human pain response. The next step is to apply this concept to more complex robots and prosthetic limbs.
“Enabling robots to feel pain will safeguard their own functionality.”
The work currently being carried out in Hannover and at Harvard is clearly still at the prototype stage. But it has far-reaching applications. Kuehn explains:
Going forward, the concept of artificial pain sensation and reaction will become vitally important to a growing number of autonomous robotic systems. Enabling such systems to feel pain will safeguard their own functionality.
Imagine an industrial robotic arm coming too close to an extreme heat source. If it is able to feel something akin to human pain, it can move away, in the same way that we instinctively withdraw our hands from flames.
With humans now working alongside a growing number of autonomous systems, robots that are sensitized to pain also could be far safer than their less intelligent counterparts.
Such robots could not only avoid painful collisions with humans and other objects, but would also be able to introspect and understand if any of their systems were dangerously defective. This is, after all, one of the facets of human pain.
Softly Does it
The evolution of devices such as the octobot also promises to revolutionize human activity and human-robot interaction. From the healthcare and military sectors to the exploration of space, robots inspired by flexible creatures such as octopuses, caterpillars or fish will increasingly perform tasks that are beyond both rigid robots and humans.
Rolls-Royce, for example, is already testing a soft, snake-like robot that can crawl inside aircraft engines, slashing days off inspection times. A soft robot fish from China’s Zhejiang University is being tested to monitor water salinity, while cephalopod-inspired robotic grippers from Boston-based Soft Robotics are already employed in many factories.
IoT and Industry 4.0 are transforming industry, giving birth to a new generation of jobs. What new roles will emerge as industrial and manufacturing processes adopt technologies such as automated robotics, VR/AR and connected machinery?
According to research from Gartner, there will be nearly 26 billion IoT devices by 2020. Meanwhile, network technology firm Cisco and engineering giant GE estimate the IoT could add $10 trillion to $15 trillion to global GDP by 2034.
But while observers focus on the technology, what do these trends mean for the workforce?
Automation certainly has its downside for employment. Up to 30% of existing UK jobs could be impacted by early 2030, estimates consultancy firm PWC. Though some job categories will disappear, new opportunities will surface as skill requirements change.
Industrial Data Scientists
Industrial data scientists extract and prepare data, conduct advanced analytics and apply the findings to improve products or production based on their special knowledge of design and manufacturing.
Dan Archer, senior consult, at high-tech recruiters ECM, says businesses are trying to attract such personnel to build data models and create meaning output from IoT data.
However, finding candidates with the right qualifications and experience is difficult. Academic and professional training is gradually catching up with industry needs, but there is still a substantial lag. Industrial companies have to recruit people with the right academic training and offer further in-house development opportunities. Archer explains:
Industrial data science has no formal career path. Data sciences itself is still young, so businesses are looking for people with a good background in maths or statistics, together with some software development skills.
Courtesy of Fraunhofer
According to IoT Analytics, the role of robot coordinator will involve overseeing robots on the shop floor and picking up the pieces in case of errors. It will involve planning and technical know-how.
For Archer, traditionally separate disciplines are merging in the field of robotics.
We have clients interested in recruiting in this area, but it is very much a candidate’s market. We see increasing crossover between roles in mechanical engineering, electrical engineering and computing.
Industrial UX Designer
How will manufacturing management understand what is taking place in their facilities? They will need user experience—UX— designers to provide intuitive production dashboards on tablets and mobile phones. These designers also will create machine interfaces and augmented reality applications. (source: IoT Analytics).
IT/IoT Solution Architect
Part IT architect and part production designer, the IoT solution architect will produce the technical specifications to integrate different technologies, platforms and people. (source: IoT Analytics).
Camille Rustici is a Video Journalist and the Editor-in-Chief for DirectIndustry e-magazine. She has years of experience in business issues for various media including France 24, Associated Press, Radio France…
Lindsay Clark is a freelance journalist specializing in computing. He has won industry awards as news editor at Computer Weekly. He has also written for newspapers including The Guardian, The Financial Times…