hazardous environments

Jet engines can have up to 25,000 individual parts, making regular maintenance a tedious task that can take over a month per engine. Many components are located deep inside the engine and cannot be inspected without taking the machine apart, adding time and costs to maintenance. This problem is not only confined to jet engines, either; many complicated, expensive machines like construction equipment, generators, and scientific instruments require large investments of time and money to inspect and maintain.&nbsp;Researchers at Harvard University&rsquo;s Wyss Institute for Biologically Inspired Engineering and John A. Paulson School of Engineering and Applied Sciences (SEAS) have created a micro-robot whose electroadhesive foot pads, origami ankle joints, and specially engineered walking gait allow it to climb on vertical and upside-down conductive surfaces, like the inside walls of a commercial jet engine. The work is reported in&nbsp;<a href="http://robotics.sciencemag.org/content/3/25/eaau3038" rel="noopener noreferrer" target="_blank">Science Robotics</a>.&ldquo;Now that these robots can explore in three dimensions instead of just moving back and forth on a flat surface, there&rsquo;s a whole new world that they can move around in and engage with,&rdquo; said first author S&eacute;bastien de Rivaz, a former Research Fellow at the Wyss Institute and SEAS who now works at Apple. &ldquo;They could one day enable non-invasive inspection of hard-to-reach areas of large machines, saving companies time and money and making those machines safer.&rdquo;The new robot, called HAMR-E (Harvard Ambulatory Micro-Robot with Electroadhesion), was developed in response to a challenge issued to the Harvard Microrobotics Lab by Rolls-Royce, which asked if it would be possible to design and build an army of micro-robots capable of climbing inside parts of its jet engines that are inaccessible to human workers. Existing climbing robots can tackle vertical surfaces, but experience problems when trying to climb upside-down, as they require a large amount of adhesive force to prevent them from falling.<iframe src="https://player.vimeo.com/video/303994124" frameborder="0" allowfullscreen="" class="fr-draggable" style="width: 772px; height: 430px;"></iframe>HAMR-E, created in collaboration with Rolls-Royce, is a micro-robot that uses electroadhesion to scale vertical, inverted, and curved surfaces, allowing it to explore spaces that are too small for humans. HAMR-E could one day be used to inspect jet engines and other complicated machines without requiring them to be taken apart. Credit: Wyss Institute at Harvard University.&nbsp;The team based HAMR-E on one of its existing micro-robots,&nbsp;<a href="https://wyss.harvard.edu/technology/versatile-ambulatory-microrobots/" target="_blank">HAMR</a>, whose four legs enable it to walk on flat surfaces and swim through water. While the basic design of HAMR-E is similar to HAMR, the scientists had to solve a series of challenges to get HAMR-E to successfully stick to and traverse the vertical, inverted, and curved surfaces that it would encounter in a jet engine.First, they needed to create adhesive foot pads that would keep the robot attached to the surface even when upside-down, but also release to allow the robot to &ldquo;walk&rdquo; by lifting and placing its feet. The pads consist of a polyimide-insulated copper electrode, which enables the generation of electrostatic forces between the pads and the underlying conductive surface. The foot pads can be easily released and re-engaged by switching the electric field on and off, which operates at a voltage similar to that required to move the robot&rsquo;s legs, thus requiring very little additional power. The electroadhesive foot pads can generate shear forces of 5.56 grams and normal forces of 6.20 grams &ndash; more than enough to keep the 1.48-gram robot from sliding down or falling off its climbing surface. In addition to providing high adhesive forces, the pads were designed to be able to flex, thus allowing the robot to climb on curved or uneven surfaces.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1569985592337-HAMR-E-whole_body-wPenny.jpg" style="width: 567px;" class="fr-fic fr-dib">HAMR-E is small but mighty, and could one day carry instruments and cameras to inspect small spaces. Credit: Wyss Institute at Harvard University&nbsp;The scientists also created new ankle joints for HAMR-E that can rotate in three dimensions to compensate for rotations of its legs as it walks, allowing it to maintain its orientation on its climbing surface. The joints were manufactured out of layered fiberglass and polyimide, and folded into an origami-like structure that allows the ankles of all the legs to rotate freely, and to passively align with the terrain as HAMR-E climbs.Finally, the researchers created a special walking pattern for HAMR-E, as it needs to have three foot pads touching a vertical or inverted surface at all times to prevent it from falling or sliding off. One foot releases from the surface, swings forward, and reattaches while the remaining three feet stay attached to the surface. At the same time, a small amount of torque is applied by the foot diagonally across from the lifted foot to keep the robot from moving away from the climbing surface during the leg-swinging phase. This process is repeated for the three other legs to create a full walking cycle, and is synchronized with the pattern of electric field switching on each foot.When HAMR-E was tested on vertical and inverted surfaces, it was able to achieve more than one hundred steps in a row without detaching. It walked at speeds comparable to other small climbing robots on inverted surfaces and slightly slower than other climbing robots on vertical surfaces, but was significantly faster than other robots on horizontal surfaces, making it a good candidate for exploring environments that have a variety of surfaces in different arrangements in space. It is also able to perform 180-degree turns on horizontal surfaces.HAMR-E also successfully maneuvered around a curved, inverted section of a jet engine while staying attached, and its passive ankle joints and adhesive foot pads were able to accommodate the rough and uneven features of the engine surface simply by increasing the electroadhesion voltage.<blockquote><figure class="quote">This iteration of HAMR-E is the first and most convincing step towards showing that this approach to a centimeter-scale climbing robot is possible, and that such robots could in the future be used to explore any sort of infrastructure, including buildings, pipes, engines, generators, and more<figcaption>ROBERT WOOD</figcaption></figure></blockquote>The team is continuing to refine HAMR-E, and plans to incorporate sensors into its legs that can detect and compensate for detached foot pads, which will help prevent it from falling off of vertical or inverted surfaces. HAMR-E&rsquo;s payload capacity is also greater than its own weight, opening the possibility of carrying a power supply and other electronics and sensors to inspect various environments. The team is also exploring options for using HAMR-E on non-conductive surfaces.&ldquo;This iteration of HAMR-E is the first and most convincing step towards showing that this approach to a centimeter-scale climbing robot is possible, and that such robots could in the future be used to explore any sort of infrastructure, including buildings, pipes, engines, generators, and more,&rdquo; said corresponding author Robert Wood, Ph.D., who is a Founding Core Faculty member of the Wyss Institute as well as the Charles River Professor of Engineering and Applied Sciences at SEAS.&ldquo;While academic scientists are very good at coming up with fundamental questions to explore in the lab, sometimes collaborations with industrial scientists who understand real-world problems are required to develop innovative technologies that can be translated into useful products. We are excited to help catalyze these collaborations here at the Wyss Institute, and to see the breakthrough advances that emerge,&rdquo; said &nbsp;Wyss Founding Director Donald Ingber, M.D., Ph.D., who is also the&nbsp;Judah Folkman Professor of Vascular Biology at Harvard Medical School and the Vascular Biology Program at Boston Children&rsquo;s Hospital, and Professor of Bioengineering at SEAS.

HAMR-E uses electroadhesive pads on its feet and a special gait pattern to climb on vertical, inverted, and curved surfaces, like the inside of this jet engine. Credit: Wyss Institute at Harvard University

New “HAMR-E” robots could enable inspection of complex machines without dismantling them

Robots with sticky feet can climb up, down, and all around

Most robots used in factories today are powerful but blind. They are programmed to do specific tasks repeatedly with high precision and speed, but until now have not been able to adapt to changes in the environment or handling variables. Robot arms often lack the ability to grasp an object if it is moved a few inches, not to mention picking or sorting millions of different products in a warehouse.As a result system integrators design shaker tables, feeders, conveyor belts, etc., so robots can be offered the same parts in the right orientation. Larger industrial robots need cages so they don’t accidentally hurt nearby people. Unlike human hands, which can perform tens of thousands of different tasks, robot arms can only be programmed for single tasks, and they need the proper end effectors.Additionally, most robots cannot sense, unless you equip them with force or vision sensors. They don’t know if tasks are performed properly, because they cannot see or feel.Traditional computer vision requires pre-registration of all objects, i.e. scanning and building computer-aided design (CAD) models for all items beforehand with expensive 3D cameras. The process is time-consuming and inflexible. Even if there was a box with exactly the same shape, but a different size, a robot couldn’t automatically recognize the differences and figure out how to grasp the new item.In addition, translucent packaging, reflective surfaces, and deformable objects (such as food and clothing) make robotic vision an even more difficult problem to solve. The additional non-robot hardware and integration end up costing four times more than a robot arm, which costs anywhere between $10,000 to $100,000.Adding intelligence to robotsTo solve these issues, deep reinforcement learning (DRL) is unleashing the full potential of robotics, giving them the ability to recognize and react to their surroundings and handle product variations. Robots can now learn from experiences with off-the-shelf cameras and deep neural networks.With enough data and practice, robots can now teach themselves new abilities, as was seen with robots’ ability to identify images and win video games. With every grasp and trial, a robot gets smarter and more adept at mastering the task. Furthermore, cloud-connected robots allow learnings to be shared with each other. This is a tremendous shift, making robotics solutions more dexterous, flexible, and scalable.Deep Learning (DL) is primarily used for image classification. Deep neural networks learn representations, rather than task-specific algorithms.Reinforcement learning (RL) is inspired by behavioral psychology. It learns control policies by trial-and-error through reward or punishment.Deep Reinforcement Learning (DRL) combines these two approaches. It is currently suited for:· Simple or simulated tasks· Fault-tolerant tasks· Just enough variation to make explicit modeling difficult· Easy-to-define goals (reward functions)· Semi-structured environmentsWarehouse as a testing ground for AIAutomation in warehouses is widely considered the “low-hanging fruit” for these technologies because tasks tend to be similar across warehouses, and the environment is more structured. For example, order picking represents more than 40% of operational costs across most warehouses. While tasks are repetitive, they involve some variation with products and packaging design, making it impossible to hard-program robots in advance.Furthermore, labor costs account for up to 70% of a warehouse’s total budget. Pressured by e-commerce companies such as Amazon, retailers are looking to automation to address labor shortages and reduce costs. Customer demand, price competition, and fast delivery requirements are driving a strong business case for warehouses to be the first adopter of AI-enabled robots.Chart: Why do we see AI-enabled robots in the warehouse first?<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNTY4OTAzMzQ5MzI3LTFfTDhkY3A1c1lfcEU0MTdqdW9VaEMwZy5wbmciLCJlZGl0cyI6eyJyZXNpemUiOnsid2lkdGgiOjk1MCwiZml0IjoiY292ZXIifX19" style="width: 766px;" class="fr-fic fr-dib"> Most tasks in a warehouse are fault tolerant, unlike tasks on a production floor or in the automotive industry. If a robot accidentally drops an object in a warehouse, it can try again as long as it achieves the required speed and success rates without damaging the goods.DRL is particularly suited for fault-tolerant simple tasks — actions a human can perform within a few seconds — with enough variation in semi-structured environments. As technology improves in environments like warehouses, it can then be applied in other industries, such as manufacturing, where tasks are more complicated and more uncertainties exist. Thus, an automated warehouse acts as an incubator, predicting a knowledge spill-over to many other market segments.Piece-picking is the holy grailWarehouse automation has been around for decades, in the form of automated storage, retrieval systems, and mobile robots like those from Kiva (now Amazon Robotics), that move items around.But most of the pick-and-pack operations within a warehouse are still performed by humans, with labor costs accounting for 50 to 70% of the overall warehouse budget. Worker shortages have driven up salaries by a rate of 6 to 8% every year, while robot costs have fallen considerably since the 1990s.Piece-picking has long been the holy grail of robotics. Year after year, incumbents such as Amazon and KUKA host robotics challenges for startups and academic teams to create machines that can identify, pick up and stow goods. The emergence of deep learning allows robots to recognize, pick, and place hundreds or up to thousands of items.But the technology is not yet perfect. It’s still challenging for a machine to recognize tens of millions of objects, and manipulate deformable objects or items with transparent packages. However, our interviews with Locus Robotics and Osaro indicate that many industry experts expect the technology will mature. In addition, we will have a robot vision camera that can recognize almost everything in a warehouse within five years. If that happens, it will affect not just warehouses, but retail, delivery, and many other applications that we haven’t yet imagined.Pushing towards standard modelsTechnology improvements in warehouse automation and beyond will also push the mature, but fragmented, robotics industry to become more standardized and modular. Given the nature of narrow AI, most Silicon Valley startups in the AI-enabled robotics industry choose to focus on specific vertical applications and collect proprietary data as a defensive advantage.Piece-picking by robots is the best example. As the technology improves, we will see warehouse piece-picking startups enter manufacturing, food, and agriculture markets. Moving away from manually programming a robot and having it learn and act autonomously on specific simple tasks — and sharing the learning — will become more important in the future.However, it’s not easy to find scalable and technically feasible business cases like piece picking that customers are willing to pay for. For example, assembly tasks vary from factory to factory, making it difficult to get sufficient training data or scale a solution across different customers.Given current technology constraints, there’s still a trade-off between precision and flexibility. Deep learning allows robots to handle variation, but these AI-enabled robots still cannot achieve the same precision and accuracy as traditional robots, at least not today.Some startups are providing modules or technology stacks for other players in the ecosystem to mitigate the complexity and scalability issues mentioned above. New areas where startups are likely to enter and disrupt include teleoperation modules, controllers that allow for safer human-robot collaboration, human-centered AI protocols, and sensors that can quantify human behavior.Eventually, we may see unified operating systems for AI-enabled robots similar to Windows or Android in the consumer electronics space, or standard user interfaces that will fundamentally transform the fragmented robotics industry and further accelerate its disruption.Standard modules and interfaces will bring down the cost to enter the market and shorten the time to market. As DRL and robotics technology improves, we will see a boom across industries including agriculture, food processing, home, and even surgical robotics.How technology will transform the industry landscapeLed by industry leaders like Amazon and Ocado, a British online grocery store, retailers see efficient and cost-effective supply chains as a key to success and are incentivized to automate their warehouses for lower cost, lower management complexity, and higher scalability. While Amazon keeps its Kiva mobile robots and automated warehouse solutions for in-house use only, Ocado launched its fulfillment platform to help other companies store, pick, and transport groceries. But most retailers still rely on material-handling companies and system integrators to build and maintain an automated warehouse.Incumbent material-handling companies tend to exploit the current technology, focusing on high-revenue-potential retrofit projects. This gives startups an opportunity to enter from the lower-end markets, where incumbents are less interested, and thus would not respond immediately. Dozens of startups offer scalable and affordable solutions that address customer needs for robots that can handle high-variability, low-precision tasks, such as piece picking in the warehouses.On the other hand, large robotics companies have long focused on developing high-speed and more-precise solutions to serve their main customers in the automotive and manufacturing industries. The pursuit of absolute precision is contrary to the process of deep learning, where results improve over time through trial and error.Some robotics companies saw an opportunity to enter new segments that require robots to handle high-variability, but lower-precision tasks, and began to build in-house AI teams and explore partnerships with startups developing deep neural network solutions for robots.There are currently more than 20 warehouse piece-picking robot startups worldwide, including Osaro and Righthand Robotics. Most of these startups (between seed round and Series C funding) are working on pilot projects with incumbent material-handling, retail, and robotics companies.Software and services will also capture more values, while premiums in hardware will decrease. With this power shift, as well as potential mergers and acquisitions, the landscape will change significantly over the next few years.The future of AI-enabled roboticsThoughts vary on the effect that AI and DRL will have on the robotics industry. One scenario is the robotics industry will consolidate because of the AI network effect, which says results improve as the amount of training data they’re given increases. This idea is that whoever owns the most proprietary data will win the competition.However, new researches in the areas of Transfer Learning, Meta Learning, and Zero-Shot Learning make it possible to learn from fewer and fewer examples, generalizing learning results across different fields. Cloud-based AI and robotics will also help accelerate learning and diffusion.As these technologies evolve, the landscape may face yet another significant change. This all starts from the warehouse!

The impact of artificial intelligence within warehouses will act as a crystal ball for AI, robotics in other industries

Why is Warehouse Automation So Important for AI Professionals?

One key element of the future production landscape is highly flexible Human-Robot Collaboration (HRC). This article describes 3 case studies which illustrate how collaborative robots change the way people will manufacture. KUKA, one of the world&#39;s largest suppliers of industrial robots, has written a free, downloadable white paper called &quot;<a href="http://bit.ly/kuka-whitepaper-US" rel="noopener noreferrer" target="_blank">Shaping future production landscapes</a>.&quot; The white paper describes &#39;megatrends&#39; that impact manufacturing and 3 key factors to designing production infrastructures that can meet the requirements of the future.&nbsp;<hr><h1>Intro</h1><h2>Human-robot collaboration&nbsp;</h2>In human-robot collaboration, the robot assists the human operator. This means: The machine does not replace the human, but complements his capabilities and relieves him of arduous tasks. These can include overhead work, for example, or the lifting of heavy loads. Autonomous, collaborative robots are also used to supply production workstations.In the ideal &#39;factory of the future&#39; there is no separation between automated and manual workstations. Humans and robots collaborate optimally &ndash; without separation and without safety fencing.<h2>Human-robot collaboration: the advantages</h2>HRC-capable robots (often labeled &#39;Collaborative Robots&#39; or &#39;Cobots&#39;) are rendered mobile and capable of performing different tasks flexibly using mobile platforms. They can thus be individually deployed at whatever location and for whatever purpose corresponds to production requirements &ndash; dependent on the required batch size, for example. Furthermore, these types of robots offer maximum flexibility by means of so-called spontaneous automation: They support a user as an assistant in the case of workload peaks and resource bottlenecks in production operations.Human-robot collaboration changes industrial production and manufacturing and can bring a number of advantages over traditional automation or manual labor:<ul><li>Increased flexibility in production</li><li>Relief of employees by performing ergonomically unfavorable work steps that could not previously be automated</li><li>Reduced risk of injuries and infections</li><li>High-quality performance of reproducible processes &ndash; without requiring type-specific or component-relevant investment.</li><li>Increased productivity and improved system complexity thanks to integrated sensors</li></ul> <h1>HRC Case Studies</h1>To give you an idea of the impact of collaborative robots in the workspace we&#39;ve gathered 3 case studies to show you the impact of these robots and the challenges they overcome. <h2>Case Study 1: Lightweight robots supporting operators in adhesive bonding processes.</h2><h2><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1566292124494-KUKA+LBR+iiwa+Duerr.jpg" class="fr-fic fr-dib" style="width: 766px;"></h2>All images courtesy KUKASystem and machine builder <a href="https://www.durr.com/en/" rel="noopener noreferrer" target="_blank">D&uuml;rr</a> uses two sensitive LBR iiwa robots in final assembly. Without a safety fence, they perform key tasks in the application of adhesive beads. This improves quality, saves time and lowers unit costs.<div data-ignore="true">At the company, humans and robots work together in final assembly without the need for physical safeguards. Sensitive lightweight robots are used for the adhesive bonding of GPS antenna covers and tanks in the vehicle body. The solutions improve the quality of the adhesive bonding result, save time and lower unit costs.&nbsp;</div>The LBR iiwa detects any fault that arises when the GPS antenna cover is loadedFor application of adhesive to the GPS antenna cover, the assembly worker places the workpiece into the robot gripper manually. The gripper sucks onto it and moves it to the adhesive nozzle on the application tower. The robot slowly moves the GPS antenna cover upwards to the application nozzle. If it encounters an obstacle, it moves back a little thanks to its collision detection ability and starts the motion over from the beginning. Only after three attempts does it move back into the starting position. Otherwise, the adhesive application process starts and the adhesive bead is applied carefully while the robot executes the path. Finally, back at the starting point, the assembly worker removes the GPS antenna cover and mounts it on the vehicle. &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;<iframe src="https://www.youtube.com/embed/PdAXCNtXabc?&wmode=opaque" allowfullscreen="" class="fr-draggable" style="width: 767px; height: 429px;" frameborder="0"></iframe>Precise adhesive beads thanks to the seventh axis of the LBR iiwaFor the automated process of gluing the tank into place in final assembly, the skilled worker guides the tank to a turntable with the aid of a manipulator. There he cleans it, moves it into the correct position and transfers it directly to the robot for further processing. When the starting point is reached on the stationary tank, the nozzle opens under pressure so that no air bubbles are created. The robot then applies the adhesive bead onto the tank very evenly. Sensors on the application head monitor the accurate height of the bead. Thanks to its seventh rotating axis, the robot glues in a radius of 360 degrees &ndash; without re-orienting or having to interrupt the bead. As soon as the robot has completed its task, the skilled worker fits the tank into the vehicle body at the specified position.<a href="http://www.durr.com/" target="_blank">D&uuml;rr</a> has already sold ten systems in the field of adhesive bonding, and is working on HRC solutions for the robot-based adhesive bonding of small washers and other components. <h2>Case Study 2: Human-robot collaboration during the adjustment of headlights.</h2><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1566292345359-Fahrassistenzsystemprfstnden_Drr.jpg" style="width: 766px;" class="fr-fic fr-dib">To reduce the strain on the workers, two KUKA LBR iiwa cobots perform the unergonomic task of adjusting fog lights at Ford. Parallel to this, human colleagues can adjust the main headlights.<article data-ignore="true">The initial situationIn the automotive industry, vehicle fog lights have previously been adjusted manually by human operators. While stooped over, the human operator searches for the hard-to-reach opening for the adjusting screws in the bumper area. Once he has found the adjusting screw, he positions the tool on it extremely carefully without damaging the adjustment opening on the bumper.</article><article data-ignore="true">The solutionTo provide relief for the human worker during this ergonomically unfavorable work and simultaneously achieve improved of the adjustment, Ford VOME (Vehicle Operation Manufacturing Engineering), D&uuml;rr Assembly Products and KUKA have jointly developed an innovative alternative concept for the conventional process as part of a feasibility study. The solution called for the use of the KUKA LBR iiwa cobot. The sensitive robot adjusts the fog lights fully automatically. In doing so, humans and robots work on the same vehicle without additional safety equipment.</article><iframe src="https://www.youtube.com/embed/9HWY-CLR3Co?&wmode=opaque" allowfullscreen="" class="fr-draggable" style="width: 766px; height: 419px;" frameborder="0"></iframe>TeamworkWhile the human operator adjusts the conventional headlights, the cobot adjusts the hard-to-reach fog lights. Two lightweight robots are already in use in four headlight/driver assistance system test stands for the new Ford Focus C519 at the Ford plant in Saarlouis. &nbsp; &nbsp; &nbsp; &nbsp;The secret of the HRC conceptWith its size and joint torque sensors, the robot detects contact immediately and reduces its level of force and speed instantly. These characteristics make it possible to work with human operators in confined spaces. Furthermore, with its high-performance servo control, the cobot detects contours quickly under force control. In combination with an end effector specially developed by D&uuml;rr (consisting of a camera system and an adjustment screwdriver), the robot positions the adjustment screwdriver according to the hole coordinates acquired by the camera system. The adjusting screw itself is located approximately 80 mm behind the hole in the bumper. Thanks to sensitive movements, the cobot optimally positions the adjustment tool into the screw head.Redundant safety is provided by the HRC-capable, heavy-duty aluminum gantry from D&uuml;rr Assembly Products &ndash; on which the KUKA LBR iiwa is positioned in a ride-on installation above the light collecting box directly in front of the headlight to be adjusted. The advantage here: additional robot positioning can be dispensed with. <h2>Case Study 3: Using a cobot to install pump wells. </h2><h2><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1566292578317-KUKAflexFellow_Platzierung_im_Arbeitsbereich_IMG_3628.jpg" style="width: 766px;" class="fr-fic fr-dib"></h2>In the future, BSH Hausger&auml;te GmbH will be using a <a href="https://www.kuka.com/en-us/products/mobility/mobile-robot-systems/kuka-flexfellow" rel="noopener noreferrer" target="_blank">KUKA flexFELLOW</a> to carry out the installation of pump wells on the dishwasher production line.&nbsp;<article data-ignore="true">The initial situationThe <a href="https://www.bsh-group.com/us/" rel="noopener noreferrer" target="_blank">BSH Hausger&auml;te</a> GmbH factory in Dillingen, Germany is Europe&rsquo;s largest and most modern factory for dishwashers. Around 10,000 machines leave the production line every day in two-shift operation. There are a total of seven production lines for manufacturing dishwashers.Screw fastening of the pump covers in the dishwasher is an ergonomically inconvenient task as the employee has to lean into the dishwasher housing to perform the task. The mechanical assistant now takes on this monotonous step in the process.&nbsp;The task &nbsp; &nbsp;&nbsp;&nbsp; &nbsp;Its contribution has already been tested successfully over several months as part of a pilot system. In addition to relieving the human operator of a cumbersome task, the robot also contributes by documenting its work and indicating whether the screws have been tightened correctly or not.The solution &nbsp; &nbsp; &nbsp; &nbsp;The key challenge when designing the system was to ensure that the manual workstation remained unchanged and that the automation solution could be integrated into the existing assembly line. Its sensitive and responsive capabilities enable it to recognize if, for example, a pump well component is not positioned correctly and then presses it into place.&nbsp;<iframe src="https://www.youtube.com/embed/jtkJQJXO7AQ?&wmode=opaque" allowfullscreen="" class="fr-draggable" style="width: 767px; height: 413px;" frameborder="0"></iframe>The advantages of using a cobot:<ul><li>Reduction of the manual workload in an ergonomically inconvenient task</li><li>Automated documentation of work steps</li><li>Indication of correct screw fastening operation</li></ul>Using its responsive capabilities, the cobot can then calibrate itself independently at its workstation, use a search run mode to find the screw positions, re-apply pressure to the component if it is not correctly positioned and finally tighten the four screws. <hr><h1> </h1><h1>Further Reading</h1><ul><li>Specifications of the <a href="https://www.wevolver.com/wevolver.staff/kuka.lbr.iiwa/" rel="noopener noreferrer" target="_blank">KUKA LBR iiwa</a></li><li>&quot;<a href="http://bit.ly/kuka-future" rel="noopener noreferrer" target="_blank"></a><a href="http://bit.ly/kuka-whitepaper-US" rel="noopener noreferrer" target="_blank">Shaping future production landscapes,</a>&quot; KUKA&#39;s white paper describing the &#39;megatrends&#39; that impact manufacturing and 3 key factors (people, technology and adaptation) to designing production infrastructures that can meet the requirements of the future.</li></ul> </article>

In human-robot collaboration, human and machine work hand in hand. The human operator controls and monitors production, the robots perform the physically strenuous work. Both contribute their specific capabilities.

Human-robot collaboration: 3 Case Studies

This article is part of a series about the usage of robots in harsh environments, written by post-doctoral robotics researcher Matthew Nancekievill. Find the second article, on subsea environments,&nbsp;here.<hr>Lets face it, there are some jobs that we just don’t want to do, or CAN’T do that we will have to get robotic platforms to complete. This is especially true of harsh environments such as subsea, mining, space, arctic, often forgotten surgical robotics and nuclear decommissioning. In this article we are going to take a brief look at robotic platforms currently deployed within the nuclear industry, why they’re required and solutions that are still required for all you innovators out there. &nbsp;With decommissioning costing the UK £3billion/yr and estimated costs of £121 billion over the next 120 years, there is a requirement for increased efficiencies and decommissioning rates that robotics can provide.&nbsp;Hopefully this article acts as a summary of robotic solutions in nuclear decommissioning without being too much of an exhaustive list.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNTU5NjY4MDk3MDA3LUltYWdlIDIucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 766px;" class="fr-fic fr-dib"><h1>A look at the Nuclear Decommissioning Environment</h1>Decommissioning happens around us all the time, old buildings get torn down, coal power plants shutdown and vehicles get scrapped. The nuclear industry is no different with the reactors, storage facilities and processing elements all requiring decommissioning when they reach the end of their useful life.Hazardous substances can be found in all the above environments with asbestos, chemicals used during refinement, rare earth metals and oils that can’t be put into our main waste stream all examples of hazardous substances. The Nuclear industry faces all the same problems but adds one to the list, “nuclear waste”.I’ve always felt that nuclear gets a bad rap in the press, with all the pollutants and oil spills throughout the years created from coal power plants seemingly ignored when nuclear waste is mentioned. However, the effects of nuclear radiation on the body can be very unforgiving.To give you a flavour, researchers working with weak radioactive sources, such as myself, are allowed a total yearly dose of &lt;1 mSv attributed to radiation work, registered radiation workers in the UK &lt;20 mSv. This is a large safety factor to account for medically proven effects of radiation at radiation levels &gt;250 mSv with 1,000 mSv likely to kill you within a few days to a couple of weeks. (Average background radiation dose in the UK is approximately 2.7 mSv)Compare this to radiation doses in some of the most radioactive places on earth, such as the UK’s Sellafield Site or the Fukushima accident, where in the most extreme cases (no really, the most extreme cases, the majority is not like this) dose-rates of around 10,000 mSv.h-1 are possible (check-out <a href="http://irid.or.jp/en/research/20150420-2/" rel="noopener noreferrer" target="_blank">these survey results</a> from the IRID and the shape-changing robot mentioned later.This is before you add in the difficulties of the physically constrained and tight working spaces, high temperatures, contaminated water used for cooling and, in the case of nuclear accidents such as Fukushima, an unknown physical layout “behind the door” due to explosions within the reactor buildings.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNTU5NjcyODIxNzYyLUZ1a3UuanBnIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 766px;" class="fr-fic fr-dib"><h1>Current Practices</h1>In less radiologically extreme environments, much of the work is carried out by human workers in air-fed suits with multiple layers of gloves, some of which could be lead-lined (lead-lined gloves) worn to avoid contamination and puncturing of the suit on sharp edges. This often means that with all the getting ready, decontamination at the end of the shift and the physical exertion required to operate in these suits, an 8-hour work shift could result in anywhere between 15 minutes to 2 hours of actual decommissioning with power tools cumbersome to use and movement awkward. Workers have been known to empty their boots at the end of their shift of all their sweat that has built up… Workers are, at the root of it, tasked with dismantling the facility. This means cleaning, chopping and moving all sorts of materials into the correct waste stream and then moving on to the next object or structure.<h2>Robotics in Nuclear</h2>It is clear that some of these repetitive tasks or highly radioactive areas lend themselves to the use of robotic platforms. There has been a large body of work conducted on developing solutions for just that. Aquatic robotic platforms for use within submerged nuclear waste storage tanks, robotic manipulators for laser cutting of structures, drone-based devices for site surveys and ground-based robots for automated warehouse characterisation and unknown environments.Examples of these are:The Forth AVEXIS, developed jointly by Forth Engineering and the University of Manchester. A submersible ROV designed to be deployed within the Magnox Swarf Storage Silo and fit through a 6” access port. More information within the video.<iframe src="https://www.youtube.com/embed/OLvAQFz5wh8?&amp;wmode=opaque&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" allowfullscreen="" class="fr-draggable" style="width: 766px; height: 443px;" frameborder="0" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true" data-gtm-yt-inspected-7="true" id="626921597" title="Avexis ROV" data-gtm-yt-inspected-29="true" data-gtm-yt-inspected-37="true"></iframe>The LaserSnake2, which combines a multi-jointed “snake-arm” manipulator with a powerful laser-cutter. Developed by OCRobotics, The Welding Institute, National Nuclear Laboratory, Laser Optical Engineering Ltd. And ULO Optics. It is designed to cut and reduce the size of objects and structures to fit in dedicated waste containers.<iframe src="https://www.youtube.com/embed/hqOfRhJsaEQ?&amp;wmode=opaque&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" allowfullscreen="" class="fr-draggable" style="width: 766px; height: 436px;" frameborder="0" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true" data-gtm-yt-inspected-7="true" id="439090068" title="LaserSnake2 - Laser cutting for nuclear decommissioning at Sellafield - a world first." data-gtm-yt-inspected-29="true" data-gtm-yt-inspected-37="true"></iframe>Researchers from Bristol University have just recently flown a drone over the Chernobyl Red Forest highlighting the site survey capabilities of drones applicable to all nuclear sites.<iframe src="https://www.youtube.com/embed/_Eto98XTm-4?&amp;wmode=opaque&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" allowfullscreen="" class="fr-draggable" style="width: 766px; height: 394px;" frameborder="0" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true" data-gtm-yt-inspected-7="true" id="334628213" title="YouTube video player" data-gtm-yt-inspected-29="true" data-gtm-yt-inspected-37="true"></iframe>Hitachi-GE have also developed a “shape-changing robot” to characterise the internals of Fukushima. Designed to be passed through small gaps in a long cylindrical shape, it is then capable of morphing into a “U” shape for stability. Equipped with a radiation tolerant camera and dosimeter, multiple robots were deployed with valuable data returned.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNTU5NjY4MzQ5NTkyLVNoYXBlLWNoYW5naW5nIElSSUQtSGl0YWNoaSByb2JvdCAtIDQ1MC5qcGciLCJlZGl0cyI6eyJyZXNpemUiOnsid2lkdGgiOjk1MCwiZml0IjoiY292ZXIifX19" style="width: 766px;" class="fr-fic fr-dib">However, one of them got stuck, which leads me to my next point.<h1>The problem with Robots</h1>I love robots, and I believe that robotic systems HAVE to and WILL have a huge part to play in harsh environments, but there are still things that have so far left deployment of robotic systems on the fringes of use. These include, but are not limited to:<ul><li>Robots are dumb: When compared to a human assessing a situation. The Hitachi shape-changing robot fell foul of a common problem with robotic systems, it got caught in a hole in the grating it was driving on it wasn’t expecting and that could not be seen by the human operator with the robot not “smart” enough to avoid or raise a flag. Robots are only as smart as we make them!</li><li>Radiation effects: Robots readily survive longer than humans but there are still failures of the electronics in high dose areas.</li><li>Tether entanglement:&nbsp;Most robots (not including drones) are often required to be connected via tether. This is for safety, in-case the robot breaks, meaning it can be unceremoniously dragged out but causes issues with entanglement.</li><li>Robots require a skilled pilot: That skill-set is not common.</li><li>The industry isn’t ready: When things have been done a certain way for a long time, it is difficult to change that. Not to mention all the legal licensing issues and who takes responsibility when something goes wrong?! Media storms surrounding the ethics of robots taking jobs and becoming our future overlords do not help (thanks a lot Terminator).</li></ul><h1>In Conclusion</h1>There is a great body of work being completed within industry and research institutions developing bespoke solutions for specific problems and there have been many successful deployments and also many unsuccessful deployments, which is all part of innovation! Not included above but deserve a mention with regards to innovation and deployments to Brokk and Seabotix robotic systems that are often used daily.To really get consistent robotic platform deployments in nuclear decommissioning, further innovation improving the capabilities of robotic platforms is required as well as upskilling of the workforce and events showcasing the technology to industry. Communication is key and the continued development of systems by all the engineers out there.<hr>This article is part of a series about the usage of robots in harsh environments, written by post-doctoral robotics researcher Matthew Nancekievill. Find the second article, on subsea environments,&nbsp;here.

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