Cobot
Assembly Line
Universal Robots unveils its AI Accelerator, enabling a new wave of AI-powered cobot innovations
Universal Robots, the Danish collaborative robot (cobot) company, presented for the first time the UR AI Accelerator – a ready-to-use hardware and software toolkit created to further enable the development of AI-powered cobot applications.
The toolkit brings AI acceleration to Universal Robots’ (UR) next-generation software platform PolyScope X and is powered by NVIDIA Isaac™ accelerated libraries and AI models, running on the NVIDIA Jetson AGX Orin™ system-on-module. Specifically, NVIDIA Isaac Manipulator gives developers the ability to bring accelerated performance and state-of-the-art AI technologies to their robotics solutions. The toolkit also includes the high-quality, newly developed Orbbec Gemini 335Lg 3D camera.
Customer Story - Cobot Palletizing with Polykar
ABB launches groundbreaking Ultra Accuracy for GoFa™ cobots
ABB Robotics launched Ultra Accuracy, a new industry-leading feature for its GoFa cobot family that delivers the highest level of precision available in cobots, enabling over 10 times greater path accuracy vs. other cobots on the market.
With its superior performance, Ultra Accuracy meets the demands of applications where exact positioning is crucial for maintaining product quality and operational efficiency. Applications include gluing and sealing in consumer electronics production, laser welding of car parts, composite material layers in aerospace manufacturing, and precision laser cutting in metals fabrication processes. It can also be used for accurate positioning of additive layers in building prototypes in 3D printing, and for performing precision quality checking in metrology applications.
Does size matter? Exploring the effect of cobot size on user experience in human–robot collaboration
In the vision of Industry 5.0, collaborative robots (or cobots) play a central supporting role in various industries, especially manufacturing. Close interaction with cobots requires special attention to user experience to fully exploit the benefits of this paradigm. Consequently, understanding the impact of a cobot’s physical size on user experience becomes critical to optimizing human–robot collaboration (HRC). This research aims to investigate the relationship between cobot size (UR3e – small cobot vs. UR10e – large cobot) and user experience in HRC contexts, in conjunction with other factors (i.e., cobot movement speed and product assembly complexity). Through a series of controlled experiments involving 32 participants, user experience data were obtained by collecting physiological measures (i.e., electro-dermal activity, heart activity, eye-tracking metrics) and subjective responses with questionnaires (i.e., perceived workload, interaction quality, and affective state). Results showed that the large cobot was generally perceived to be safer, more natural, efficient, fluid, and trustworthy. With the large cobot, there was a decrease in dominance; however, it was offset by the learning effect. Perceived workload was mainly influenced by product complexity. No clear difference in terms of mental strain emerged from the physiological data comparing the cobot sizes. In addition, the interaction term between cobot size and cobot movement speed never emerged as significant. The results of this research can offer practical insights to improve the effectiveness and acceptance of cobots during the implementation phase.
7-Axis Cobots Feature “World’s First” Integration of Controller Into the Base
Kassow Robots released its Edge Edition 7-axis cobot that features a reduced footprint and is suitable for use in locations with limited floor space or mobile applications.
The Kassow Robots team reduced the size of its traditional external robotics controller to allow it to be integrated into the base of its Edge Edition robots. The new controller’s footprint measures only 160 x 200 millimeters, and its volume has been reduced by 90% compared to the classic controller.
The defining feature of Kassow Robots’ KR series and Edge Edition Cobots is located at the top of the J2 arm.
This unique feature can prevent a robot from reaching a singularity and alarming out during operation. A singularity occurs when two joints are aligned or near the edge of the travel limits. Depending on the type of motion that is defined when programming, singularities may not be able to be avoided.
For example, if the robot has to enter a small compartment, a linear move may be the only option to prevent a crash, but this can cause a single axis to exceed its limits. With this additional axis, the robot now has more flexibility during programming and can prevent unnecessary alarms for new programmers.
SWR-TIPTIG Cobot for Gas Tungsten Arc Welding
FANUC’s New CRX-10iA/L Paint: World’s First Global Ex-Proof Collaborative Paint Robot
Global automation leader FANUC America unveils the new CRX-10iA/L Paint collaborative robot at Automate 2024. As the first explosion-proof collaborative paint robot for use and sale globally, FANUC’s CRX-10iA/L Paint cobot will unlock the benefits of automation for more companies in the painting, powder and/or gel coating with fiberglass reinforcement industries. The new FANUC cobot not only will help boost all types of paint operations including high-mix, low-volume applications, but also is designed to comply with the stringent explosion-proof safety standards required in the United States.
The CRX-10iA/L Paint cobot has a payload of 10 kg as well as the longest reach in its class at 1,418mm, allowing the cobot to access large workpieces in even the most difficult of places that can pose ergonomic challenges for humans to manually reach. Featuring the same smooth and rounded design of the CRX series, the CRX-10iA/L Paint cobot is lightweight at 45 kg and has a small footprint, which can be further enhanced by stacking the control unit onto a light and compact R-30iB Mini Plus controller. Along with the other CRX cobots, the CRX-10iA/L Paint is maintenance-free for 8 years adding to ownership savings and boosting operations.
Two-Platen System for Die-Casting Production
10 cobots guarantee ‘just in time’ manufacture of gearboxes
Gearbox manufacturer SEAT Componentes needed to automate the unloading of 18,000 machined gears a day at its plant in Spain to guarantee the quality of the parts. The company integrated 10 collaborative robots from Universal Robots using only internal resources.
This formula made it possible for SEAT to keep know-how on cobot configuration in-house, eliminating extra programming and maintenance costs. The do-it-yourself installation was done without changing the existing factory layout, allowing new applications to be configured in less than 1 hour. As a result, the company has reduced errors, improved worker safety, and now has a team prepared to take on new automation projects.
Cobot creates ‘cell manufacturing dream’ for plastics thermoformer
Thermoforming, a technology that is more than a century old, uses sheet plastic that is heated to become soft so it can be vacuum-formed in or around a mold. Excess plastic is then cut off to create final products with dimensions that range from a few inches to the size of a room.
When Kal Plastics needed to replace a CNC machine that was nearing the end of its life, Goff was presented with an opportunity. She set out to research the use of cobots for her own business and agreed to share her findings at the organization’s national conference. “I did my homework and found that Universal Robots was the global leader in the collaborative robot space,” Goff said. “They came out and gave us a demonstration, and when I looked at the numbers, they were really attractive. I was looking at getting another five-axis CNC router, and at the time it would have been a $250,000 investment and I would have waited 12 months to take delivery. When I met with UR, I was quoted two weeks to get the equipment, and the entry point was a quarter or a fifth of the cost.”
Audio-Visual Effects of a Collaborative Robot on Worker Efficiency
Collaborative workplaces are increasingly used in production systems. The possibility of direct collaboration between robots and humans brings many advantages, as it allows the simultaneous use of human and robotic strengths. However, collaboration between a collaborative robot and a human raises concerns about the safety of the interaction, the impact of the robot on human health, human efficiency, etc. Additionally, research is unexplored in the field of the collaborative robot’s audio-visual effects on the worker’s efficiency. Our study results contribute to the field of studying collaborative robots’ audio-visual effects on the worker’s behavior. In this research, we analyze the effect of the changing motion parameters of the collaborative robot (speed and acceleration) on the efficiency of the worker and, consequently, on the production process. Based on the experimental results, we were able to confirm the impact of robot speed and acceleration on the worker’s efficiency in terms of assembly time. We also concluded that the sound level and presence of a visual barrier between the worker and robot by themselves have no effect on the worker’s efficiency. The experimental part of the paper clearly identifies the impact of visualization on work efficiency. According to the results, the robot’s audio-visual effects play a key role in achieving high efficiency and, consequently, justifying the implementation of a collaborative workplace.
2 collaborative robots freeing up 10 employees per production shift
IDEMIA: How a global leader in identity leverages AWS to improve productivity in Manufacturing
At IDEMIA, the flywheel started by prioritizing and grouping high-value and low-hanging use cases that could be implemented quickly and easily. The Cobot use cases were selected because they provided a clear business impact and had low technical complexity. Deploying these use cases in production generated a positive ROI in a short period of time for IDEMIA. It not only increased the profitability and efficiency of the industrial sites but also created a positive feedback loop that fostered further adoptions and investments. With the benefits generated from this initial use case, IDEMIA had the opportunity to reinvest in the IoT platform, making it more robust and scalable. This mitigated risks, lowered costs for the next use cases, and improved the performance and reliability of the existing ones. Demonstrating tangible benefits of Industrial Internet of Things (IIoT) solutions expanded adoption and engagement across IDEMIA’s organization, fostering a culture of continuous improvement and learning.
Connected Digital Manufacturing: Cobots and Augmented Reality for Electronics Assembly
LightGuide’s industrial augmented reality (AR) work instruction platform seamlessly integrates with a wide variety of digital manufacturing technologies, factory tools, and IO devices, including cobots. Here, LightGuide is integrated with KUKA’s LBR iisy cobot to combine the benefits of industrial automation and digital work instructions to streamline the process of assembling an electrical component.
How Technology Developments Can Impact Quick Response Manufacturing
Enterprises in the industrial sector looking to maintain their relevance and competitive edge—especially in environments with irregular, changing and unpredictable demands—should explore the Quick Response Manufacturing (QRM) methodology. Looking forward, this methodology, which was developed in the early 1990s by Prof. Rajan Suri of the University of Wisconsin-Madison, could be revamped with the use of new technologies, such as artificial intelligence (AI) and collaborative robots (cobots).
At its core, QRM is a company-wide strategy to reduce lead times in all aspects of an organization’s operations. QRM’s primary focus is not just the production floor but encompasses the entire organizational and production process, from the initial inquiry to the product’s delivery. QRM emphasizes time as the most critical metric. The idea is simple: reduction in lead times leads to an increase in competitiveness and market share.
Automated packaging tech helps streamline snack and bakery operations
Kellogg’s uses packaging automation to create efficient production lines with the capacity for high throughput volume. This entails using automation in areas where manual labor may struggle to keep up with rapid rates of product output. “Our automation systems handle tasks such as placing products into containers and transporting them to the end of the line, as well as filling unit loads and loading them onto trucks via forklifts. The product mostly remains untouched by human hands until it reaches the retailer,” says David Sosnoski, director of packaging engineering for salty snacks, Kellogg Co.
Robotics plays a significant role within Kellogg’s packaging automation initiatives, offering a diverse range of options, from basic and simple robots to advanced collaborative robots (cobots). “Cobots are designed to replace repetitive human tasks that do not require a larger, fully automated solution,” Sosnoski says. “They have proven valuable in filling the middle ground between tasks that are too complex for traditional automation but exceed human capabilities in certain areas.”
🦾 Doosan Robotics to develop GPT-based collaborative robots
Doosan Robotics, a subsidiary of South Korea’s Doosan Group specializing in robot solutions, is venturing into the development of collaborative robot solutions using AI-based GPT (generative pre-trained transformer) technology to enhance its software capabilities.
Doosan Robotics announced it has entered into a business agreement with Microsoft and Doosan Digital Innovation to develop a GPT-based robot control system” utilizing Microsoft’s Azure OpenAI service. Azure OpenAI provides cloud services that include cutting-edge open AI systems, including GPT.
Doosan Robotics plans to apply GPT to its collaborative robots, enabling them to autonomously correct errors and perform tasks. Once the solution is developed, programming time will be reduced, leading to improved operational efficiency and utility.
Automation that displays flashes of creativity
More complex icing and decorating systems are replacing traditional waterfall icing operations. For example, Inline Filling Systems recently developed a swirled icing decoration on top of a fully baked cake. The system relies on servo pump fillers feeding a pair of eight-across nozzle manifolds attached to two ABB robots applying a distinctive, programmable decoration pattern over an Auto-Bake Serpentine production line.
The Deco-Bot is a self-contained robotic decorating, glazing, depositing and spraying system with a built-in conveyor and quick hookup for heated and non-heated pumps. “Cobots are not the speed demon robotics you see on a caged line. They serve a different purpose,” he explained. “They help manufacturers with the labor crisis with a small footprint while being easy to clean and set up, and they are very safe.” It’s not uncommon to see 10 to 12 cobots decorating cakes night and day on the same production line.
GreyOrange Ranger Assist - Assisted Picking CoBot (warehouse automation solution)
🦾 Xaba and Rolleri Partner to Develop a Cognitive Autonomous Cobot Workcell
Xaba, developers of xCognition, the first AI-driven robotics and CNC machine controller, today announced a collaboration with Rolleri Holding SpA focused on the development of a cognitive, autonomous collaborative robot (cobot) workcell for welding operations in manufacturing. The collaboration enables the integration of xCognition with Rolleri Robotic cobots.
To showcase the benefits of xCognition, Xaba and Rolleri recently completed ISO 9283 tests in Xaba’s robotic lab. A FARO Vantage Laser Tracker System was used to acquire all data needed to train the xCognition machine learning model and to validate trajectory accuracy improvements. The successfully completed tests showed 10 times performance improvements in absolute positioning and trajectory accuracy, and five times improvements in relative positioning and trajectory accuracy. As a follow up to the initial tests, Xaba and Rolleri will be undertaking Tig and Laser welding tests to further validate welding quality improvements such as improved accuracy and repeatability.
Sanding Cobot Delivers 40% Increase in Throughput at Andrew Pearce Bowls
Cobots Install Cable Ties
The cobot program for installing the cable ties was designed in Polyscope, Universal’s programming software. The program works for two different harness assembly boards.
Finally, we did an ergonomic analysis of the new cable tie installation process using RULA and JSI. After measuring the angles of various body parts, the values of Groups A and B were calculated according to RULA. The value for Group A was 3, and the value for Group B was 4, resulting in a final score of 4. This score is significantly lower than the original manual operation. Similarly, the JSI for the automated station was 4.5, which is lower than the risk level for the manual operation. Our project clearly shows that cable tie installation task could be automated, improving ergonomics.
High Mix Low Volume Manufacturing Automation with Collaborative Applications
🦾 Factory Visit: Investment bankers tour client’s robot-filled machine shop
“Many shops can’t get the parts out because their quality control has gone from four days to six weeks. They just don’t have the staff and it becomes a major bottleneck in the company,” Dave Henderson explains. New Scale’s Q-Span workstation is a robotic arm that has grippers on the end that can pick up parts and then measure them using an automated dimensional gauging system.
“We saw a need for lower cost, easier to use, less risky, and more flexible automation to allow small- and medium-size enterprises to leverage automation just as the big guys have for decades,” according to Josh Pawley. “The shortage of welders and skilled fabricators is the biggest driver of our business,” says Pawley. “It’s largely the nature of welding – it’s dull, dirty and dangerous in many cases. There are not a lot of folks going into the space, and the average age of a welder is in the late 50s. But the most dull and dirty jobs can be supplemented with automation.”
“Incremental automation is very important, the ability to break it down into step-by-step pieces,” Henderson says. “We consistently get requests from people who were thinking of heavy integration, but they haven’t had any automation before, and they wanted a turnkey system which cost $1 million and take a year to implement. “But traditional automation for some fabricators is too much to jump into to begin with. We can get them up and running in three months for $100,000. By doing that you empower your staff to operate machines, as opposed to having turnkey systems that are dependent on the system integrator. So you get the best out of both automation and your people.”
Lights-Out 3D Printing
Injection Molding Machine Unloading with a ROKAE Robot
Labor shortages have forced manufacturers to adopt collaborative technology
Robotic screwdriving differs from more traditional applications, such as fixed or handheld screwdriving. Among other things, robots make it easy to do quick changeovers and run small, varying size batches of related assemblies. In addition, robots can drive screws from all directions without ergonomic concerns and with varying degrees of torque. They also have the ability to drive different sizes of screws using various feeders for each type of fastener. Manufacturers can achieve higher cycles per screwdriver spindle and faster cycle time per screw, while improving quality.
“[Automated] screwdriving used to be a task that was complex, costly and took up a large footprint on the assembly line,” explains Leclerc. “As such, it was reserved for use in vast plants with big automation budgets producing in high volumes. “There are screwdriving systems that can be bought off the shelf, shipped within a few business days, easily installed and adapted to production changes,” claims Leclerc. “It’s a completely new era.”
Lights-out Manufacturing with Athena 3D
Techman Robot Announces Its All-in-One AI Cobot Series
Techman Robot has announced the introduction of its TM AI Cobot series. AI Cobot is a Collaborative Robot, which combines a powerful and precise robot arm with native AI inferencing engine and smart vision system in a complete package, ready for deployment in factories, accelerating the transition to Industry 4.0.
TM AI Cobot works on the principle of being smart, simple and safe. By combining visual processing in the robot arm, the AI Cobot can perform fast and precise pick and place, AMR, palletizing, welding, semi-conductor and product manufacturing, AOI inspections and food service preparation, among many other applications that can be accelerated by AI-Vision.
Comau develops advanced collaborative robotics as part of the Sherlock Project
Comau has recently completed the development of several innovative human-centered robotic applications as part of its collaboration within the SHERLOCK project (Horizon 2020 Framework Programme, grant agreement 820689 – coordinated by Laboratory for Manufacturing Systems & Automation, University of Patras) – to promote effective industrial human-robot collaboration. Under the scope of the project, Comau has designed a series of user cases featuring advanced collaborative robotics enhanced with sensors, smart mechatronics and AI-based cognition. In doing so, the company has created efficient human-robot collaboration modules that feature AURA (Advanced Use Robotic Arm), the company’s high-payload collaborative robot arm, Racer-5 COBOT, a 6-axis articulated robot that can work at industrial speeds of up to 6 m/s when human operators are not present, and Comau’s wearable MATE exoskeleton. Comau is helping create modular collaborative robotic cells that can be quickly and easily deployed within a wide range of industrial settings.
Loading glass is a tough and delicate job.
— Universal Robots (@Universal_Robot) September 20, 2022
Let robots do it 🦾
Learn how Matsunami Glass increased production by 50% and improved working conditions for its employees:
➡️ https://t.co/4OEeUxyF7A#glass #manufacturing #automation pic.twitter.com/9DnTTvEu5X
SoftBank-backed Chinese robot maker, JAKA, to build plant in Toyota's backyard
JAKA is one of a number of companies looking to challenge Denmark-based Universal Robots’s lead in collaborative robots, also called co-robots, which play a complementary role to the hulking machines on automated assembly lines. Other contenders include Japan’s Fanuc and Chinese startup Elite Robot. JAKA’s advantage comes from the size of its home market, as well as its track record as a Toyota supplier. The company’s mean time between failure is 80,000 hours, the equivalent of one incident every nine years or so.
JAKA now makes all of its robots in Changzhou, China, at a factory with an annual capacity of about 10,000 units. For JAKA, the Nagoya plant is not only about serving Japanese buyers. In preparation for the expansion, JAKA Robotics raised a total of 1 billion yuan ($148 million) from investors including SoftBank Vision Fund 2 and Prosperity7 Ventures, a fund under Saudi Aramco.
Han’s Robot to Help Revolutionize Auto Parts Production
It is possible for Han’s Elfin collaborative robot to easily detect the air-tightness of around 2,000 automotive waterproof connectors day-to-day via human-machine collaboration. Furthermore, the robot could make use of laser equipment to concurrently execute operations like 3D visual scanning inspection and QR code marking on the workpiece, thereby finishing the complete process in just 30 seconds.
Primarily, the detection accuracy of such robots exceeds manual inspection, completely fulfilling the production needs of enterprises.
Collaborative robot programming with MachineLogic
High-Torque Screwdriving Solution [ESTIC × Universal Robots]
Cobot tutorial - Hand-E adaptive grippers - How to program a pick and place
Collaborative Robotics in Manufacturing Assembly
Assembling transformed materials into components is a key step in the manufacturing process. Due to growing product complexity and variety, there is a need for the design of components that are constructed out of a variety of materials for diverse functional purposes alongside aesthetic value. Moreover, trends in manufacturing and industry are toward mass customization in highly competitive global markets, with assembly a key value-added activity at the end of the supply chain.
Collaborative robots (cobots) are a key development in the field of robotics that show vast potential for multiple industries, including manufacturing. Technologies such as artificial intelligence, machine learning, neural networks, and sensors (such as vision, contact, torque, and force detecting sensors) have given Cobots improved interaction with their environment. This has facilitated a new paradigm in robotics where operators and robots work together to share tasks.
Marlan Lets Cobot Perform Heavy Repetitive Sanding Work
One of the operations that are common when processing solid surface products is sanding. This is heavy, repetitive work that requires skilled personnel. Such personnel is becoming increasingly difficult to find. In addition, it is important that the quality is guaranteed. It became increasingly difficult for Marlan to organize this task properly. The company therefore went in search of a way to automate this process as much as possible.
After delivery, the cobot was deployed within two weeks. Heerema was able to program it within half an hour, without any programming experience. After the implementation and installation, two employees were trained and the cobot was fine-tuned to determine the correct pressure when sanding. This step was also the start of further optimizing other parts of the production. According to Heerema, some employees were immediately enthusiastic, but others were afraid of losing their jobs. “But that’s not what we’re about at all. We want to make it easier for employees and give them the opportunity to increase their output.” The employees are now fully accustomed to the cobot and see it as a kind of colleague.
The cobot at Marlan is currently used for sanding bathtubs. This is a large object that is difficult to sand manually. A major problem here is monitoring consistent quality. Heerema: “But with a cobot you can guarantee an even pressure which also ensures constant product quality.”
This Factory Is Using AR To Help With A Hiring Crunch
One of the challenges associated with AR has been in trying to turn a complex physical process, such as wiring a component or working a machine, into code that could run on a headset. Taqtile CEO Dirck Schou said the company’s software makes programming for AR glasses simple, and based on my conversation with Tim Lecrone and Beau Wileman of PBC, the software Taqtile developed is easy to use. Once PBC has created a module for training it pays for itself after 1.44 employees train with it according to Wileman.
The cobots help handle processes that are repetitive and free up people to take on different tasks. Given how tough it is to hire people to work in the factory, using them helps reduce the overall staffing load. But the biggest gains so far have been in training and getting employees quickly up to speed. Now PBC can hire a person and get them working on a machine in a few days as opposed to that taking up to six weeks. It also helps reduce the cost of training a cobot and staff. Wileman told me that an intern, which costs $17 an hour, can train a cobot or map out a process in less than four hours, while it might cost around $30,000 for an outside expert to manually train a cobot.
Plug-and-Play Robot Ecosystems on the Rise
Robot ecosystems are bringing plug-and-play ease to compatible hardware and software peripherals, while adding greater value and functionality to robots. Some might argue that the first robot ecosystem was the network of robot integrators that has expanded over the last couple decades to support robot manufacturers and their customers. Robot integrators continue to be vital to robotics adoption and proliferation. Yet an interesting phenomenon began to take shape a few years ago with the growing popularity of collaborative robots and the industry’s focus on ease of use.
Campbell describes the typical process for engineering a new gripping solution for a robot: “You have to first engineer a mechanical interface, which may mean an adapter plate, and maybe some other additional hardware. If you’re an integrator, it must be documented, because everything you do as an integrator you have to document. You have to engineer the electrical interface, how you’re going to control it, what kind of I/O signals, what kind of sensors. And then you have to design some kind of software.
“When I talk to integrators, they say it’s typically 1 to 3 days’ worth of work just to put a simple gripper on a robot. What we’ve been able to do in the UR+ program is chip away at time and cost throughout the project.”
Improving Cycle Time with Veo FreeMove – Estimating the Benefits with a General Example
In our model, the design and operation of the application will determine how and how often the human and robot will collaborate. At one extreme, there is no collaboration, and the application runs unattended throughout the operating cycle. At the other end, human interactions can occur multiple times a cycle, as in a parts presentation for assembly application. We concluded that the shorter the cycle time and the more frequent the required human interaction the more collaborative the application.
Making Welding Accessible to All
With the ongoing shortage of skilled workers and the pickup in the economy, suppliers of welding equipment are finding ways to making welding easier for those working in manufacturing. Automation is the leading technique among many.
“Manual welding is an area with a very high degree of repetitive motion injury, resulting in turnover and associated costs,” he said. “OSHA puts out a statistic that says any investment in safety yields a six-to-one payback. So, robotic welding is an investment in safety, as well as productivity and quality. Take all these factors into account and you get a pretty big payback number.”
Innovation Fuels Stanley Black & Decker's Transformation
With more than 100 manufacturing plants globally, the 178-year-old Stanley Black & Decker (SBD) has entrenched itself one of the world’s most recognizable and innovative brands.
A key component of the company’s staying power? The company has stayed on a clear journey of continuous improvement with dedication to innovation that includes regularly applying advanced technologies across the company’s operation, ultimately resulting in a culture dedicated to seeking “game changing solutions” that consistently yields an impressive number of new products and world firsts each year.
Collaboration requires presence sensing
The challenge of automation has always been to keep people safe while trying to produce more product in the same footprint. The faster a machine runs, the more physical space is required to guarantee that, if something goes wrong, the machine has enough time to come to a complete and safe stop before potentially making contact with humans or other machines around it. Traditionally, this would involve a physical cage around the piece of automation. This cage could take the form of a frame with either polycarbonate or expanded steel (fence) panels.
Made to physically defend a person from getting too close, these types of guarding systems also take up a lot of real estate. For this reason, they are not well-suited to a cobot application where we don’t want the new automated device taking up any more space than the human it is replacing.
The technology required to respond to this need for an ever tighter operating envelope has advanced dramatically, especially over the past two or three years. While we will delve into that momentarily, it is important to note that the robot manufacturers, in addition to coming up with new ways to sense the presence of people in proximity to the robot, have had to come up with ways to safely limit the range of operation to be inside the normal operating range of the robot.
Using tactile-based reinforcement learning for insertion tasks
A paper entitled “Tactile-RL for Insertion: Generalization to Objects of Unknown Geometry” was submitted by MERL and MIT researchers to the IEEE International Conference on Robotics and Automation (ICRA) in which reinforcement learning was used to enable a robot arm equipped with a parallel jaw gripper having tactile sensing arrays on both fingers to insert differently shaped novel objects into a corresponding hole with an overall average success rate of 85% with 3-4 tries.
Can a cobot offer the flexibility of a human on the shop floor?
Since the Great Recession more than a decade ago, metal fabricators aren’t necessarily employing people unless they are absolutely needed. Manufacturing companies are lean, which helps to keep fixed costs down and the business more manageable when business slows.
It’s also a gamble. Unless shop floor personnel are cross-trained, the absence of a machine operator can sabotage productivity goals for the day. While more automated bending systems are being sold to North American fabricators, many shops still require an operator to sit in front of the press brake to get parts formed.
Teradyne and Universal Robots Announce Agreement for Teradyne to Acquire Universal Robots, Leader in Collaborative Robots
Teradyne, Inc. (NYSE:TER) and the shareholders of Universal Robots (UR) today announced they have signed a definitive agreement under which Teradyne will acquire privately held Universal Robots, the Danish pioneer of collaborative robots, for $285 million net of cash acquired plus $65 million if certain performance targets are met extending through 2018. The acquisition has been approved by the Board of Directors of each company and is expected to close in the second quarter of 2015 subject to customary closing conditions and regulatory approval.
COBOTS: US5952796A
An apparatus and method for direct physical interaction between a person and a general purpose manipulator controlled by a computer. The apparatus, known as a collaborative robot or “cobot,” may take a number of configurations common to conventional robots. In place of the actuators that move conventional robots, however, cobots use variable transmission elements whose transmission ratio is adjustable under computer control via small servomotors. Cobots thus need few if any powerful, and potentially dangerous, actuators. Instead, cobots guide, redirect, or steer motions that originate with the person. A method is also disclosed for using the cobot’s ability to redirect and steer motion in order to provide physical guidance for the person, and for any payload being moved by the person and the cobot. Virtual surfaces, virtual potential fields, and other guidance schemes may be defined in software and brought into physical effect by the cobot.