Autonomous Mobile Robots employed for material handling; Credits: Teradyne

This article offers an in-depth view of AMR robots, their underlying technology, and applications crucial in today's rapidly evolving technological landscape.

Understanding AMR Robots: A Comprehensive Guide

In a groundbreaking partnership that promises to reshape the landscape of automated assembly, Autoblocks and ASG have joined forces, ushering in a new era of efficiency and precision. This collaboration brings together the expertise of two industry leaders, with Autoblocks' cutting-edge platform seamlessly integrated with ASG's revolutionary Auto Feed System. The result? A game-changing fusion of innovation that empowers businesses to create customized automated assembly machines in a matter of minutes.&nbsp;ASG, short for Assembly Solutions Group, has been at the forefront of automation technology for years. Their Auto Feed System is renowned for its precision, reliability, and advanced features. By integrating this system with Autoblocks, the possibilities for automated assembly have expanded like never before.&nbsp;Efficiency Meets PrecisionThe partnership between Autoblocks and ASG is all about achieving the perfect balance between efficiency and precision. With the Autoblocks Platform and ASG's Auto Feed System, businesses can create assembly machines that not only work faster but also with an unprecedented level of accuracy.Imagine a scenario where a task that once took hours of manual labor can now be completed in a fraction of the time, without compromising on quality. This is the promise that Autoblocks and ASG bring to the table, and it's a game-changer for industries that rely on automated assembly processes.&nbsp;Customized Solutions at Your FingertipsOne of the standout features of this collaboration is the ease with which businesses can customize their automated assembly machines. Autoblocks' user-friendly interface empowers users to design machines tailored to their specific needs. Whether it's for the electronics, automotive, or any other industry, the flexibility offered is unparalleled.Thanks to this partnership, businesses can create automated assembly systems that are precisely tuned to their requirements, ensuring a perfect fit for their unique processes. The days of settling for one-size-fits-all solutions are over.&nbsp;Setting the New Standard for InnovationThe combination of Autoblocks and ASG is not just a partnership; it's a commitment to pushing the boundaries of what's possible in automated assembly. The result is a synergy that elevates the automation game to a whole new level.Whether you're seeking to streamline your production line, reduce manual labor, or improve the quality and consistency of your products, Autoblocks and ASG are your partners in innovation.&nbsp;Exploring the Future of AssemblyTo get a glimpse of what the future of assembly looks like, visit our website and explore the incredible partnership between Autoblocks and ASG. This collaboration promises to change the way industries approach automation, making it more accessible, customizable, and efficient than ever before.&nbsp;Don't miss the opportunity to be a part of this exciting revolution in automated assembly. Autoblocks and ASG are here to help your business reach new heights by setting a new standard for innovation in the world of assembly. The future is now, and it's waiting for you to be a part of it.

Autoblocks and ASG Partner Up for Automated Assembly!

Autoblocks and ASG have joined forces, ushering in a new era of efficiency and precision.

Revolutionizing Automation: Autoblocks and ASG Unite for Automated Assembly

DEEP Robotics, a global pioneer in the development and industrial application of quadrupedal robots, announced the launch of its X30 quadruped robot, a flagship product designed to meet core industry needs in multiple fields, including inspection, emergency rescue, fire detection, and more.

DEEP Robotics launches X30 quadruped robot to meet varied industry needs

Enhancing Efficiency with AGVs and AMR

AGV vs AMR: A Comprehensive Comparison in the World of Automation

This article originally appeared in <a href="https://news.mit.edu/2023/new-technique-helps-robots-pack-objects-tight-space-1017" target="_blank" rel="noopener noreferrer">MIT News</a> and has been republished with permission.<hr>Anyone who has ever tried to pack a family-sized amount of luggage into a sedan-sized trunk knows this is a hard problem. Robots struggle with dense packing tasks, too.For the robot, solving the packing problem involves satisfying many constraints, such as stacking luggage so suitcases don’t topple out of the trunk, heavy objects aren’t placed on top of lighter ones, and collisions between the robotic arm and the car’s bumper are avoided.Some traditional methods tackle this problem sequentially, guessing a partial solution that meets one constraint at a time and then checking to see if any other constraints were violated. With a long sequence of actions to take, and a pile of luggage to pack, this process can be impractically time consuming. &nbsp;&nbsp;MIT researchers used a form of generative AI, called a diffusion model, to solve this problem more efficiently. Their method uses a collection of machine-learning models, each of which is trained to represent one specific type of constraint. These models are combined to generate global solutions to the packing problem, taking into account all constraints at once.<iframe width="640" height="360" src="https://www.youtube.com/embed/mhtYU7IevtE?&amp;wmode=opaque&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" frameborder="0" allowfullscreen="" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true">&nbsp;</iframe>Their method was able to generate effective solutions faster than other techniques, and it produced a greater number of successful solutions in the same amount of time. Importantly, their technique was also able to solve problems with novel combinations of constraints and larger numbers of objects, that the models did not see during training.Due to this generalizability, their technique can be used to teach robots how to understand and meet the overall constraints of packing problems, such as the importance of avoiding collisions or a desire for one object to be next to another object. Robots trained in this way could be applied to a wide array of complex tasks in diverse environments, from order fulfillment in a warehouse to organizing a bookshelf in someone’s home.“My vision is to push robots to do more complicated tasks that have many geometric constraints and more continuous decisions that need to be made — these are the kinds of problems service robots face in our unstructured and diverse human environments. With the powerful tool of compositional diffusion models, we can now solve these more complex problems and get great generalization results,” says Zhutian Yang, an electrical engineering and computer science graduate student and lead author of a <a href="https://arxiv.org/pdf/2309.00966.pdf" target="_blank" data-lf-fd-inspected-kn9eq4roawkarlvp="true">paper on this new machine-learning technique</a>.Her co-authors include MIT graduate students Jiayuan Mao and Yilun Du; Jiajun Wu, an assistant professor of computer science at Stanford University; Joshua B. Tenenbaum, a professor in MIT’s Department of Brain and Cognitive Sciences and a member of the Computer Science and Artificial Intelligence Laboratory (CSAIL); Tomás Lozano-Pérez, an MIT professor of computer science and engineering and a member of CSAIL; and senior author Leslie Kaelbling, the Panasonic Professor of Computer Science and Engineering at MIT and a member of CSAIL. The research will be presented at the Conference on Robot Learning.<h2>Constraint complications</h2>Continuous constraint satisfaction problems are particularly challenging for robots. These problems appear in multistep robot manipulation tasks, like packing items into a box or setting a dinner table. They often involve achieving a number of constraints, including geometric constraints, such as avoiding collisions between the robot arm and the environment; physical constraints, such as stacking objects so they are stable; and qualitative constraints, such as placing a spoon to the right of a knife.There may be many constraints, and they vary across problems and environments depending on the geometry of objects and human-specified requirements.To solve these problems efficiently, the MIT researchers developed a machine-learning technique called <a href="https://diffusion-ccsp.github.io/" target="_blank">Diffusion-CCSP</a>. Diffusion models learn to generate new data samples that resemble samples in a training dataset by iteratively refining their output.To do this, diffusion models learn a procedure for making small improvements to a potential solution. Then, to solve a problem, they start with a random, very bad solution and then gradually improve it.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1697557883397-ezgif-5-a827fde90a.gif" style="width: 766px;" class="fr-fic fr-dib">Using generative AI models, MIT researchers created a technique that could enable robots to efficiently solve continuous constraint satisfaction problems, such as packing objects into a box while avoiding collisions, as shown in this simulation. Image: Courtesy of the researchersFor example, imagine randomly placing plates and utensils on a simulated table, allowing them to physically overlap. The collision-free constraints between objects will result in them nudging each other away, while qualitative constraints will drag the plate to the center, align the salad fork and dinner fork, etc.Diffusion models are well-suited for this kind of continuous constraint-satisfaction problem because the influences from multiple models on the pose of one object can be composed to encourage the satisfaction of all constraints, Yang explains. By starting from a random initial guess each time, the models can obtain a diverse set of good solutions.<h2>Working together</h2>For Diffusion-CCSP, the researchers wanted to capture the interconnectedness of the constraints. In packing for instance, one constraint might require a certain object to be next to another object, while a second constraint might specify where one of those objects must be located.Diffusion-CCSP learns a family of diffusion models, with one for each type of constraint. The models are trained together, so they share some knowledge, like the geometry of the objects to be packed.The models then work together to find solutions, in this case locations for the objects to be placed, that jointly satisfy the constraints.“We don’t always get to a solution at the first guess. But when you keep refining the solution and some violation happens, it should lead you to a better solution. You get guidance from getting something wrong,” she says.Training individual models for each constraint type and then combining them to make predictions greatly reduces the amount of training data required, compared to other approaches.However, training these models still requires a large amount of data that demonstrate solved problems. Humans would need to solve each problem with traditional slow methods, making the cost to generate such data prohibitive, Yang says.Instead, the researchers reversed the process by coming up with solutions first. They used fast algorithms to generate segmented boxes and fit a diverse set of 3D objects into each segment, ensuring tight packing, stable poses, and collision-free solutions.“With this process, data generation is almost instantaneous in simulation. We can generate tens of thousands of environments where we know the problems are solvable,” she says.Trained using these data, the diffusion models work together to determine locations objects should be placed by the robotic gripper that achieve the packing task while meeting all of the constraints.They conducted feasibility studies, and then demonstrated Diffusion-CCSP with a real robot solving a number of difficult problems, including fitting 2D triangles into a box, packing 2D shapes with spatial relationship constraints, stacking 3D objects with stability constraints, and packing 3D objects with a robotic arm.Their method outperformed other techniques in many experiments, generating a greater number of effective solutions that were both stable and collision-free.In the future, Yang and her collaborators want to test Diffusion-CCSP in more complicated situations, such as with robots that can move around a room. They also want to enable Diffusion-CCSP to tackle problems in different domains without the need to be retrained on new data.“Diffusion-CCSP is a machine-learning solution that builds on existing powerful generative models,” says Danfei Xu, an assistant professor in the School of Interactive Computing at the Georgia Institute of Technology and a Research Scientist at NVIDIA AI, who was not involved with this work. “It can quickly generate solutions that simultaneously satisfy multiple constraints by composing known individual constraint models. Although it’s still in the early phases of development, the ongoing advancements in this approach hold the promise of enabling more efficient, safe, and reliable autonomous systems in various applications.”This research was funded, in part, by the National Science Foundation, the Air Force Office of Scientific Research, the Office of Naval Research, the MIT-IBM Watson AI Lab, the MIT Quest for Intelligence, the Center for Brains, Minds, and Machines, Boston Dynamics Artificial Intelligence Institute, the Stanford Institute for Human-Centered Artificial Intelligence, Analog Devices, JPMorgan Chase and Co., and Salesforce.

MIT researchers are using generative AI models to help robots more efficiently solve complex object manipulation problems, such as packing a box with different objects. Image: Courtesy of the researchers

Researchers coaxed a family of generative AI models to work together to solve multistep robot manipulation problems.

New technique helps robots pack objects into a tight space

<h3 id="isPasted">Let’s explore some methods on how to achieve this.</h3>First and foremost, there exists the “Straightforward Programming” approach. This means: getting a skilled person to meticulously describe a task, to such an extent that one can write either a simple script or an intricate algorithm that can guide the robot to do the task. This method is great and highly effective when the task is well-defined and specific, something often done in industrial automation. However, the complexity can escalate rapidly, making it challenging. Thus, if the approach is successful, that’s excellent – but if not, we must ponder – what alternative strategies can we employ?Secondly, an alternative approach to consider is “Programming by Demonstration“. This method involves guiding the robot in performing the task. By equipping the robot with advanced force sensing capabilities and vision algorithms, this technique can prove to be quite effective. However, it’s crucial to note that its effectiveness is reliant on the robot’s abilities. Usually, robots are equipped with rudimentary grippers rather than adept, dexterous hands, which can limit the complexity of tasks they can perform.&nbsp;Okay, so how can we effectively record human actions for a robot to mimic?Ideally, we’d guide a human through the task, document it in detail, and then replay it to the robot. We might even consider feeding this information into a machine-learning system, enabling it to learn from our human-guided demonstration. Alternatively, at the very least, we can analyze these human activities, deconstruct them into simpler parts, and use this information to develop more efficient algorithms in the way that a song is deconstructed in a recording studio.&nbsp;OK, so how about, filming the person doing the task and using “machine vision” to track what they are doing?It’s certainly a good starting point. This approach provides valuable insights into the nuances of human behaviour – such as hand-switching moments, object-holding techniques, and tool usage – But our experience is that it’s really hard to track human movement&nbsp;using cameras. You need clear lines of sight, and you’ll have lots of trouble tracking the fine movements of the fingers and hands.&nbsp;Even the most advanced image-based tracking systems, while capable of monitoring hands with minimal occlusion, fail to consistently track all joint movements. Consequently, the resultant data tends to be somewhat inconsistent and noisy.&nbsp;Alright, what about using motion capture?Motion capture systems, commonly employed in film production and sports science, operate by attaching easily visible markers to the individual, such as passive elements like white dots or active elements like pulsed LEDs. This method certainly helps with the accuracy of tracking. However, it doesn’t entirely overcome the previously mentioned issues related to occlusion. Additionally, calibrating the optical systems to an error margin of less than a few millimetres is quite challenging – which means that if the task involves intricate movements, such as rolling a pen between fingers, it’s likely it’ll miss a lot.&nbsp;&nbsp;Okay. I need it to be accurate, what’s my best option then?For precise human movement tracking, your best bet is to use a tight-fitting movement-tracking&nbsp;<a href="https://www.shadowrobot.com/shadow-hand-glove/" target="_blank">glove</a>. This glove can incorporate a multitude of techniques to achieve such a feat, some even providing additional features to assist the operator (and some that make it more difficult for the operator). For instance, some gloves can relay a sense of weight, touch, or stiffness, all functionalities grouped under the term ‘haptics.’ The realm of haptics is broad, including diverse technologies from ultrasound devices transmitting signals to fingers, electrical skin stimulation, vibrating piezoelectric elements, to inflating air balloons, miniature motors, or linear actuators, among many others.Gloves that measure human hand movement can do it by utilising:<ul><li dir="ltr">Sensors that fit around the joints and track the specific movement of the joint</li><li dir="ltr">Mechanical linkages that go from one end of the finger to the other and track the whole movement of the finger</li><li dir="ltr">Inertial sensors (that clever combination of accelerometer, gyroscope and possibly magnetometer) - worn at various points on the hand to follow the movement</li><li dir="ltr">Wireless measuring sensors - detecting the location of the fingers relative to a source worn on the hand somewhere.</li><li dir="ltr">Cameras that look away from the hand and track the movement of the world. (I’m not sure I’ve seen this one used in anger but I’m sure it’s possible!)</li></ul> Even then several variations of these technologies exist. For instance, some sensors measure the flex of a glove, correlating it to joint movement. Other types of sensors stretch and track their own deformation to gauge distance. Occasionally, mechanical linkages are placed over individual joints for precise motion tracking.&nbsp;Each of these methods presents a unique approach to capturing and interpreting human movement<h3 id="isPasted">Our experience:</h3>From our extensive experience, we have found that accurately measuring the mechanical properties of the human hand can be challenging, as it often leads to significant inaccuracies. The placement of the measurement sensor is crucial, and unfortunately, the potential for slippage is high – gloves and similar apparatus tend to shift excessively, complicating the data collection. Relating the measurements to the actual rotation of a finger joint’s axis, especially the thumb, is another daunting task!<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjk3NTM2Nzk3ODE3LWxvbmcgLSBQb2xoZW11cyAmIFNoYWRvdyAoMTkyMCB4IDEwODAgcHgpLmpwZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width: 766px;" class="fr-fic fr-dib">Mechanical linkages, although valuable, can quickly become cumbersome. There is also a risk that they could discomfort the operator to the point where task completion becomes impossible (too heavy, too rigid etc). Inertial sensors present a viable option; however, (once again) preventing them from drifting is generally difficult, and the precision level they offer often falls short of what we needWe have found that wireless measurement sensors, particularly those from&nbsp;<a href="https://www.shadowrobot.com/shadow-robot-polhemus/" target="_blank">Polhemus</a>, give us excellent results. These sensors entail a transmitting source worn on the palm and receivers located at the fingertips, providing us with high-quality data for hand movement tracking. However, there remains the challenge of locating the hand within the wider three-dimensional space. For this, we have found that the HTC Vive is an excellent solution and so you will often see the Vive tracker featured in our demonstrations.Now – what we want is to accurately know where to put the robot hand – which isn’t quite the same thing as knowing accurately where the human hand is. We have to take the data from the human hand and map it to the robot hand. This is a kinematic challenge – the movements of the human and the movements of the robot don’t agree entirely, and we need to convert one to the other. The best method for mapping human data to a robot hand will depend on the specific application. For example, if you need to control a robot’s hand in real-time, then direct mapping may be the best option. If you are only interested in controlling a robot’s hand for offline analysis, then inverse kinematics or hybrid mapping may be more feasible options. Needless to say, the more complex the robot the more challenging this becomes. Lucky for us complex robots are a speciality at Shadow!&nbsp;So, the human wears a set of gloves, and they control the robot to do the task. After completing a few rudimentary training tasks the operator gets the hang of the process and they are doing it pretty well. What do we do to learn from this?We can precisely monitor the instructions sent to the robot and reproduce them. This is ideal when operating in a controlled environment where all variables remain consistent – a scenario commonly found in an automation setting within a quality assurance laboratory. In the past, we employed this technique to build a functional robotic kitchen. While it allows you to execute repetitive tasks, it lacks the ability to cope with variation.We can capture and analyze data from numerous tests, assessing them for consistency. If the results are largely similar, they can be directly applied. However, if they vary a lot, we can delve into our algorithm toolbox to try and understand these discrepancies. This is where it helps to have a <a href="https://www.shadowrobot.com/artificial-intelligence-machine-learning/" target="_blank">wide range of data</a> from <a href="https://www.shadowrobot.com/dexterous-hand-series/" target="_blank">the robot</a>, from force, <a href="https://www.shadowrobot.com/shadow-robot-11-lessons-about-tactile-sensors/" target="_blank">touch</a>, and joint sensors. The question arises: Can we employ data from vision, such as cameras aimed at the work area, to discern what’s different? To be effective, this vision data needs to be synchronized with the robot sensor data, necessitating a shared framework for all data streams.We can gather data from multiple tests and use it by “Feeding it to the AI” – meaning use it to instruct a machine learning system on how to replicate similar movements from similar data.This can be done in several ways.We might train a traditional learning model on the datasets so that similar inputs generate similar outputs. Alternatively, if we have enough data, we could use a transformer model to generate movements. We can even break down the data into smaller segments and train a network to assemble these fragments into the correct sequences.Given the impressive capabilities of modern machine learning systems in generating text, images, video, and even code, this approach appears highly promising – and it’s only the beginning!So, does this sound like it could help with a problem that you face? If it does, then let’s have&nbsp;<a href="https://www.shadowrobot.com/blog/data-humans-to-robots/hand@shadowrobot.com" target="_blank">a chat to</a> see if the Shadow Robot team can help!

Humans excel at manual tasks, and ideally, robots should surpass us in these functions. We have the advantage due to our superior dexterity, and we can perform tasks that robots should, in theory, be capable of.
As we advance robotics our goal is to effectively transfer our human skills to robots.

Getting Data from Humans to Robots

Exploring Cutting-Edge Research with the LIMO Robot

Boston University Uses LIMO Robot For Research

The Power of PrecisionThe heart of any automated system is its ability to precisely control movement and operations. Autoblocks™ has taken this to the next level with the Turn Block™ indexing table, which offers unmatched capabilities for managing operator loading, robots, power, air, communication, and safety.&nbsp;Build and Price Your MachineAt Autoblocks™, we put the power in your hands. You have the ability to design and price your machine according to your specific requirements. With Turn Block™ indexing tables available in two sizes – 24" and 36" – you can tailor your automation setup to meet your exact needs.&nbsp;Key FeaturesHere are some of the key features that make Turn Block™ a standout choice for manufacturing automation:&nbsp;1. Customizable Control:Program the speed, direction, and angle of indexing to meet your specific manufacturing needs.This base block serves as the control center for machine power, safety, air, and communication, providing a streamlined and efficient operation.&nbsp;2. Coordination at Its Best:Seamlessly coordinates operator loading and interfaces with up to 3 machine blocks, ensuring a synchronized workflow.&nbsp;The table is available in acrylic, aluminum, and steel, offering flexibility for various applications.&nbsp;3. Durability and Stability:The Turn Block™ is built on a strong and stable steel bench-top chassis, complete with locating pins for precision processes.Electronics are housed in an easily accessible, removable drawer for hassle-free maintenance.&nbsp;4. Safety First:Designed with safety in mind, the Turn Block™&nbsp;is light curtain and door switch-ready and prewired for added convenience.Part presence sensors enable effective part tracking, enhancing the overall safety and efficiency of your operations.&nbsp;5. Data Traceability:Stay in control with data traceability using a bar code scanner and data capture/retrieval.Easily mount machine enclosures directly to the Turn Block™, streamlining your manufacturing setup.&nbsp;6. Speed &amp; Torque:With a maximum table speed of 20 RPM and a maximum torque of 5.4 in-lbs. at max speed,&nbsp;Turn Block™&nbsp;ensures both speed and precision in your manufacturing processes.&nbsp;7. Warranty:Autoblocks™ stands behind its product with a 12-month warranty against manufactured defects, providing peace of mind for your investment.&nbsp;In a world where efficiency, precision, and adaptability are essential, Autoblocks™&nbsp;Turn Block™ indexing table offers a cutting-edge solution that empowers manufacturers to take their automation to new heights. Whether you're looking to enhance productivity, improve safety, or streamline your processes, Turn Block™&nbsp;is the answer.&nbsp;Autoblocks™&nbsp;continues to lead the way in industrial automation, and the Turn Block™ indexing table is a testament to their commitment to innovation and excellence. As industries evolve, Autoblocks™ remains at the forefront, offering solutions that redefine manufacturing automation. Build and price your machine today and experience the future of automation with Autoblocks™.

Explore our automation building blocks for soldering, brazing, screw fastening, induction, assembly, inspection and much more.

In the ever-evolving landscape of manufacturing and automation, efficiency and precision are paramount. Autoblocks™ understands this fundamental need and has introduced the groundbreaking Turn Block™ indexing table, a game-changer in the world of industrial automation.

Introducing Autoblocks™ Turn Block™ Indexing Table: Revolutionizing Manufacturing Automation.

Effective time management is essential when conducting inspections on container ships, as it directly influences the cost-effectiveness and competitiveness of maritime cargo transportation. Inspection plays a&nbsp;crucial&nbsp;role in ensuring container ship safety, averting cargo damage,&nbsp;maintaining&nbsp;compliance with environmental rules, and preserving the vessel's value.&nbsp;Ensuring the safety and dependability of container ships involves employing fundamental methods such as contact-based Ultrasonic Thickness (UT) inspections and visual assessments.&nbsp;These inspections proactively&nbsp;identify&nbsp;potential issues before they escalate into significant concerns, thereby aiding in the prevention of maritime mishaps.&nbsp;&nbsp; Regularly inspecting cargo vessels becomes a complex task due to their significant size,&nbsp;necessitating&nbsp;careful maneuvering to access various compartments, structures, and cargo holds.&nbsp;Traditional approaches, like rope access and scaffolding, come with inherent risks and time consumption. Addressing these hurdles, innovative flying robots have&nbsp;emerged&nbsp;as&nbsp;an optimal&nbsp;solution for ship inspections.&nbsp;Avestec's&nbsp;intelligent airborne robot, SKYRON, effectively addresses the difficulties&nbsp;encountered&nbsp;in ship inspections.&nbsp;Watch the video above to see how SKYRON performed UT and visual inspections on a container ship in Vancouver, Canada. It focused on checking the back wall of the cargo hold, the guides for the columns, and the ship's side facing the water. This inspection happened while the ship was parked at the port to unload cargo, highlighting the importance of saving time. SKYRON is a highly advanced flying robot designed for various inspections, reducing risks for&nbsp;humans&nbsp;and cutting down on inspection time and costs.&nbsp;

Watch How Flying Robots Like SKYRON Are Redefining Safety Checks at Sea 

From Robo-Flyers to Smart Scans, Unveiling the Future of Vessel Safety and Performance

<div data-id="9908f31" data-element_type="widget" data-widget_type="heading.default" id="isPasted"><h2>International Space and Robotics Contest</h2></div>For the first time in the history of the University of Applied Sciences Northwestern Switzerland FHNW, a team of nine Bachelor students from three different fields of study successfully participated in the European Rover Challenge (ERC). Within a year, the students built a Mars rover and placed 6th in the competition out of 19 teams from all over Europe, being the only newcomer in the top 10. 'It was a bit like a ‘fish out of water’ experience because we didn’t have any inside knowledge of the competition', explains Nadine Richard- the 5th-semester mechanical engineering student was in charge of the gripper, deep sampling, and the robotic arm.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjk2MjQ0NjcyNzA2LW1hcnMtcm9ib3QtM2QtcHJpbnRlZC0zLmpwZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width: 766px;" class="fr-fic fr-dib"><img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjk2MjQ0NjgxMTM4LW1hcnMtcm9ib3QtM2QtcHJpbnRlZC0yLmpwZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width: 766px;" class="fr-fic fr-dib"><img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjk2MjQ0NjkwMTc5LW1hcnMtcm9ib3QtM2QtcHJpbnRlZC0xLmpwZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width: 766px;" class="fr-fic fr-dib">The Mars rover of the FHNW in action at the European Rover Challenge (ERC)<h2>Success with the right goals</h2>For the first participation in the ERC, it was important for the FHNW team to be able to compete with a functioning rover. In the four disciplines of navigation, probing, maintenance, and science, the Mars rover had to prove its skills.&nbsp;<blockquote>'In the development, we focused especially on the drivetrain, as well as the manipulator (robotic arm and gripper), since these two components are elementary for all four tasks in the competition,' emphasizes Nadine.</blockquote><div data-id="c866847" data-element_type="widget" data-widget_type="heading.default" id="isPasted"><h2>Components from the 3D printer</h2></div>3D printing played a key role in the development of the rover. 'A big advantage of additive manufacturing is the complexity of the parts you can design, as well as the different technologies and materials ready to use,' Nadine explains. For the tires and the signal mast, the team used the FDM printers available at the university. Due to the high demands on the gripper, selective laser sintering (SLS) was used as another 3D printing technology. High durability – due to forces from all directions – and extreme lightness – due to the gripper’s center of gravity being far out – led the students to Sintratec. 'The sponsored components from Sintratec exceeded all our set requirements and performed excellently in all four tasks of the competition', Nadine happily points out.See these incredible images below that showcase the rover and gripper.&nbsp;<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjk2MjQ0NzUxMjI0LXNscy0zZC1wcmludGluZy1tYXJzLXJvYm90by5qcGciLCJlZGl0cyI6eyJyZXNpemUiOnsid2lkdGgiOjk1MCwiZml0IjoiY292ZXIifX19" style="width: 766px;" class="fr-fic fr-dib"><img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjk2MjQ0NzU3NzY5LXJvdmVyX2luX3RoZV9GSE5XX3dvcmtzaG9wLmpwZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width: 766px;" class="fr-fic fr-dib"><img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjk2MjQ0NzYzMjM2LWdyaXBwZXJfbW91bnRlZF9jbG9zZXVwLmpwZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width: 766px;" class="fr-fic fr-dib">An important element on the Mars rover is the gripper on the manipulator, which is under high loads from all directions.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjk2MjQ0ODAzMDc3LW1hcnMtcm9ib3QtM2QtcHJpbnRlZC00LmpwZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width: 300px;" class="fr-fic fr-dib"><img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjk2MjQ0ODA4NDkzLW1hcnMtcm9ib3QtM2QtcHJpbnRlZC01LmpwZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width: 300px;" class="fr-fic fr-dib"><img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjk2MjQ0ODEyMTE3LW1hcnMtcm9ib3QtM2QtcHJpbnRlZC02LmpwZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width: 300px;" class="fr-fic fr-dib">The gripper was 3D printed from lightweight and durable PA12 with the Sintratec SLS technology.<div data-id="f17ceb6" data-element_type="widget" data-widget_type="heading.default" id="isPasted"><h2>SLS convinces tomorrow’s engineers</h2></div>Nadine Richard’s team was impressed with the high durability, stability, and accuracy of the SLS components printed with PA12 on the Sintratec S2. The lack of support structures also made it advantageous for the project. Sintratec provided guidance and allowed them to incorporate new technology into their project. Nadine plans to use SLS technology for future robotic projects. Learn more about the project in the video below.<iframe width="640" height="360" src="https://www.youtube.com/embed/Ia4PSyXHeYo?&amp;wmode=opaque&amp;rel=0" frameborder="0" allowfullscreen="" class="fr-draggable"></iframe>

Students from the University of Applied Sciences Northwestern Switzerland (FHNW) build a functional Mars rover using SLS 3D printed parts and take 6th place at the European Mars Rover Challenge (ERC) in Poland.

SLS technology on a mission to Mars?

Welcome to the New World of Automation - Building Blocks for Fast and Affordable Automation!I&#39;m thrilled to take you on a journey through the evolution of AutoBlocks, an innovation designed to transform the landscape of industrial automation.In the realm of industrial automation, the last five years have seen a remarkable journey of innovation and transformation. Our team embarked on this path with a clear vision - to explore the boundaries of manufacturing and robotic automation. Drawing from the deep expertise of Fancort in advanced manufacturing, we envisioned a novel way to cater to the unique needs of clients in the Electronics and Aerospace sectors.Our journey was characterized by relentless passion and the pursuit of innovation. We undertook the ambitious task of constructing machines of increasing complexity. This endeavor has been not only enriching for our team but also instrumental in creating cutting-edge solutions for some of the world&#39;s foremost manufacturers.However, amid these successes, we encountered a significant challenge. The complexity of our systems, while delivering exceptional performance, limited our capacity to reach a broader market. It became apparent that there was a pressing need for scalable, semi-custom solutions that didn&#39;t demand exorbitant budgets or extended timelines.Conversations with industry peers revealed a common theme - the absence of a structured approach in the automation industry. It was akin to a child given a vast assortment of building blocks but no blueprint. The potential was immense, yet the outcomes often lacked sophistication.In response to these challenges, we are proud to introduce a pioneering solution - AutoBlocks. This platform represents a fundamental shift in how we perceive automation. AutoBlocks is built on the foundation of modular components, including indexing turntables, motion-additive machine blocks, and specialized application kits. It embodies the essence of flexible, scalable automation.Our collaboration with industry giants like Epson and Cognex signifies the beginning of a promising journey. But this is just the start. Our pipeline is teeming with exciting additions set to debut in early 2024. AutoBlocks is poised to become the preferred platform for future-proof automation solutions.AutoBlocks transcends being a mere product; it symbolizes the future of industrial automation. We invite you to join us on this transformative journey. Together, let&#39;s usher in a new era of innovation, efficiency, and accessibility in the realm of manufacturing and robotics.

Welcome to the new world of Automation - Building Blocks for Fast and Affordable Automation! 

A New Era in Industrial Automation

<h2 dir="ltr" id="isPasted">Introduction</h2>In the world of engineering, the integration of the Internet of Things (IoT), robotics, and artificial intelligence (AI) is transforming the capabilities of autonomous systems. This article focuses on the importance of connectivity in enabling robots to access and exchange data, leading to more intelligent and adaptable systems.&nbsp;IoT allows robots to connect to networks, while robotics involves the design and operation of autonomous machines. AI enhances IoT-enabled robots by analysing data and making informed decisions. Sensor technology, connectivity modules, and AI processing units are key components in this integration.&nbsp;<h2 dir="ltr">Understanding IoT, Robotics, and AI</h2>When we talk about integrating IoT devices with robotics and adding a layer of AI in the system, it is necessary to understand the basic differences between AI, IoT, and robotics and how they form a base for IoT-enabled robotics. These three terms are the enablers of advanced robotics, impacting how IoT-enabled robots interact with the environment. For that reason, let's break down these concepts in simple terms.<h3 dir="ltr">IoT</h3>The IoT refers to a network of physical objects that are embedded with sensors, software,&nbsp;<iframe id="64e98b97d7967caf24910157" width="250" class="specs-iframe" height="440" src="https://wevolver.com/iframe/specs/sparkfun-mgm240p-thing-plus-matter-development-board?iframe=true" frameborder="0" scrolling="false" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true"></iframe> and other technologies to connect and exchange data with other devices and systems over the internet. This exchange of data expands the possibilities for automation, monitoring, and control. While IoT is primarily focused on connectivity and data exchange, it does not inherently possess autonomous decision-making capabilities.<h3 dir="ltr">Robotics</h3>Robotics is the science and technology involved in designing, constructing, and operating robots. Robots are autonomous or semi-autonomous machines that can perform complex tasks, interact with their environment, and manipulate objects. Unlike IoT devices, which primarily focus on connectivity and data exchange, robots are physical entities capable of interacting with the physical world. While some robots may be equipped with IoT capabilities, not all robots are inherently part of the IoT ecosystem.In robotics, the IoT presents an opportunity for integrating advanced robots into broader networks, enabling them to act in a more intelligent and autonomous manner. The IoT has transformed robotics with the paradigm shift known as <a href="https://www.frontiersin.org/articles/10.3389/frobt.2020.00104/full" target="_blank">Internet of Robotic Things (IoRT)</a>.<h3 dir="ltr">AI</h3>AI encompasses the development of intelligent systems that can perform tasks requiring human-like intelligence. AI algorithms enable machines to analyse data, identify patterns, make predictions, and even make decisions based on available information. AI augments the capabilities of IoT and robotics by providing advanced data analysis capabilities and enabling autonomous decision-making. While AI can be integrated with IoT devices and robots to enhance their functionality, not all AI systems are directly part of the IoT ecosystem.<h2 dir="ltr">The Role of AI in the Convergence of Robotics and IoT</h2>AI is the core of this convergence between robotics and IoT. While IoT provides the mechanism for connecting robots and gathering data, AI is the engine that processes, learns from this data, and enables autonomous decision-making.&nbsp;For instance, <a href="https://www.conurets.com/use-of-iot-and-robotics-in-daily-life/" target="_blank">an AI-powered IoT robot</a> could leverage machine learning algorithms to recognize patterns in the data, learn from them, and make predictions or decisions based on its learnings. This combination of IoT connectivity and AI-based learning results in a new breed of intelligent, autonomous robots capable of complex operations without requiring constant human oversight.&nbsp;&nbsp;<iframe id="64e98edcf7cd7caf266afb28" width="250" class="specs-iframe" height="440" src="https://wevolver.com/iframe/specs/arduino-uno-rev-4-boards?iframe=true" frameborder="0" scrolling="false" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true"></iframe>However, not all robots are inherently part of the IoT. A robot becomes an IoT device when it's equipped with sensors and connectivity capabilities that allow it to collect, transmit, and receive data over the internet. In essence, it's the ability to participate in the larger, interconnected ecosystem of data and devices that makes a robot an IoT device.&nbsp;<h2 dir="ltr">The Mechanics of IoT in Robotics and AI</h2>Three primary technological areas are integral to this interconnected system: sensor technology, connectivity modules, and AI processing units.<h3 dir="ltr">Sensor Technology</h3>By combining many sensors—including cameras, radars, lidars, and ultrasonic sensors—designers can create data that is merged into a single model of sensor fusion to create a robust sense function. As the Internet of Vehicles (IoVs) and edge intelligence are used for training and real-time environment models, the sense functions are evolving towards distributed model-based or AI-inference processing at the sense-node and in the central cognition.&nbsp;<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjk1NzQ2NDMzODU2LXNodXR0ZXJzdG9ja18yMjgwMzczNjgxICgxKSAoMSkuanBnIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 300px;" class="fr-fic fr-dib">Figure 2: Robotic vision camera sensors enable seamless navigation, object recognition, and enhanced situational awareness.&nbsp;The advancement of sensor technology in the IoRT system's capacity to sense the environment using a variety of sensor types, combine the information from the various sensors, and localize itself and other things using GPS/GNSS signals and both local and high-definition maps to create a semantic understanding and local and global models. Because perception information is the input for analytics and AI processing, the data that these sensors acquire must be in a format that can be used by various and unique cognitive processes of robotic things and applications.<h3 dir="ltr">Connectivity Modules</h3>Connectivity is the lifeblood of the IoT, facilitated by communication modules that enable data exchange between devices. These modules employ a variety of technologies, including Wi-Fi®, Bluetooth®, Zigbee, <a href="https://www.wevolver.com/article/an-introduction-to-lorawan" target="_blank">LoRaWAN</a>, and cellular networks.&nbsp;<iframe id="66757846af77e394067bd518" width="250" class="specs-iframe" height="440" src="https://wevolver.com/iframe/specs/broadcom-afbr-s50-fek-evaluation-kit?iframe=true" frameborder="0" scrolling="no" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true"></iframe>In terms of connectivity, wireless communication methods are dominant for IoRT. When discussing the interactions and pairings of wireless technologies (such as cellular 5G and beyond), IoT/IIoT, and AI approaches and processes, the term "intelligent connectivity" is used.The connectivity of modules for IoT-enabled robotics involves developing robotic objects with reliable wireless and cellular connectivity is essential. IoRT applications may use wired, wireless, cellular, optical, audio, video, voice, or other types of communication channels. Any of a wide range of protocols—including TCP, UDP, 802.15.1, 802.15.4, 802.11, 4G/LTE/5G—can be used as the foundation for the communication networks.Edge-distributed processing, including analytics at the edge based on AI concepts and approaches, replaces centralised processing for mission- and safety-critical IoRT applications where latency, dependability, and throughput are crucial requirements. Edge-distributed processing makes use of multi-access edge computing, fog computing, and intelligent connection offered by wireless and cellular communication (4G/5G and beyond). This idea enables IoRT apps to process data locally and use local learning to apply AI algorithms to the data that has been acquired, reducing the need to transport huge volumes of data to the cloud, store data locally, and lighten the stress on connection lines.<h3 dir="ltr">AI Processing Units</h3>AI processing units, also known as AI accelerators, constitute the brainpower behind IoT-enabled robots. The progress of IoRT depends heavily on the AI processing units. The capabilities of particular robotic objects are improved by the AI algorithms. To improve cognition and decision-making, AI technologies are used to optimise the sensor fusion capabilities of IoRT devices (such as cameras for detecting sight, chemical sensors for identifying smell and taste, microphones for hearing, pressure sensors for detecting touch/pressure). They are also used to extract patterns from data. To give analytics and insights and to optimise the functions of the individual robotic things and their cooperative behaviours as a fleet, AI techniques and approaches are incorporated in the various layers of IoRT platforms.Deep neural networks, such as convolutional neural networks (CNNs), are used to assess and extract visual features from images. To improve the performance of the recognition function by attaining high detection rates of quality variations or probable errors, the strategies are created for partitioning and de-noising monitored signals. IoRT applications can now handle extraordinarily huge data sets because of the transition from central compute to edge/fog nodes. To significantly increase the computing efficiency of an inspection model that can identify the type and <a href="http://www.ijmmm.org/vol7/445-ICMEM2019-216.pdf" target="_blank" data-lf-fd-inspected-kn9eq4roawkarlvp="true">severity of defects</a>, this method is also used in the case of effective manufacturing inspection systems. It combines AI techniques with edge processing by adapting a CNN model to the fog computing environment.At the level of robotic things, video capture, video data compression, video picture pre-processing, and segmentation are performed using perception tools like cameras. Better object identification accuracy can be achieved by jointly training a context and scenery-aware adaption model using data from various video capture systems. An ideal offloading method must be established in order to balance the distribution of the deep learning (DL) computation among IoRT devices, edge servers, and the cloud. The trade-offs between important indicators such network health, video compression, data rates/usage, power consumption, processing delay, frame rate, and processing accuracy of analytics must be taken into account. Numerous distributed edge robotic thing devices can work together at the edge to provide better services.&nbsp;The system's overall performance can be enhanced by edge computing federation and distribution of functions for compressing the DL model at the edge layer. According to <a href="https://ieeexplore.ieee.org/abstract/document/8337810" target="_blank">a research on object detection in edge computing</a>, the cloud can guarantee the integration of distributed learning models with the edge computing layer and update the parameters of these models on edge devices. The computing power and global knowledge in the cloud infrastructure can be used for processing and assisting the edge nodes in updating DL models when the edge infrastructure is unable to provide a reliable service with the required quality (e.g., detecting objects/patterns with low confidence).<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjk1NzQ2NDgzMjM3LXNodXR0ZXJzdG9ja182NjgyMDI5ODUtc2NhbGVkLmpwZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width: 300px;" class="fr-fic fr-dib">Figure 3: The automation of robot arms within IoRT revolutionizing the manufacturing, logistics, logistics, and assembly processes. Image credit: KukaMouser Electronics, an authorised global distributor of electronic components, offers a wealth of products and knowledge that support the development of IoT-enabled robotics and AI systems.&nbsp;These products range from advanced microcontrollers and processors to sensors, connectivity modules, power management devices, and much more. By supplying these essential elements, Mouser is facilitating the development and deployment of IoT-enabled robotics and AI systems across various industries.<h2 dir="ltr">Conclusion</h2>The integration of the IoT with advanced robotics and AI is revolutionizing the capabilities of autonomous systems. Robots connected to IoT networks gain access to a wealth of data and the ability to communicate and collaborate with other devices, leading to more intelligent and adaptable systems.&nbsp;The addition of AI further enhances the capabilities of these IoT-enabled robots, enabling them to learn, reason, and make informed decisions based on real-time data analysis. Together, IoT, robotics, and AI are reshaping industries and everyday life, offering new opportunities for innovation and automation.&nbsp;As engineers and designers embark on the development of IoT-enabled robotics and AI devices, Mouser Electronics serves as a reliable partner, providing the tools to compare and acquire the necessary components for these groundbreaking technologies. Through their comprehensive inventory and user-friendly website, Mouser supports the advancement of IoT-enabled robotics and AI, driving progress and shaping the future of intelligent and autonomous systems.<h2 dir="ltr">References:</h2><a href="https://www.frontiersin.org/articles/10.3389/frobt.2020.00104/full" target="_blank">https://www.frontiersin.org/articles/10.3389/frobt.2020.00104/full</a><a href="https://geekflare.com/digital-transformation-ai-robots-iot/" target="_blank">https://geekflare.com/digital-transformation-ai-robots-iot/</a><a href="https://www.analyticssteps.com/blogs/internet-robotic-things-robotics-iot" target="_blank">https://www.analyticssteps.com/blogs/internet-robotic-things-robotics-iot</a><a href="https://iot.eetimes.com/the-internet-of-robotic-things-how-iot-and-robotics-tech-are-evolving-together/" target="_blank">https://iot.eetimes.com/the-internet-of-robotic-things-how-iot-and-robotics-tech-are-evolving-together/</a><a href="https://ieeexplore.ieee.org/abstract/document/8976180/" target="_blank">https://ieeexplore.ieee.org/abstract/document/8976180/</a>

The integration of AI, IoT, and robotics allows robots to access and exchange data with other devices, enabling them to make informed decisions.


The Role of IoT in Robotics and AI: Understanding Connectivity

An investigation into innovative applications of SBCs


SBCs for Modern Engineering

Building robots is hard.Even if you start with a manufactured platform for locomotion, the work ahead can be challenging and time-consuming. How many sensors will require a power supply and data routing? What EDGE processing is needed? How will a remote operator interface with the machine? What coding will allow everything to work in unison and ensure the best data and performance possible? How will data be transmitted or stored?That’s the hard stuff, which inevitably requires a fair bit of time and effort. &nbsp;Typical robotics development is lengthy, it can take anywhere from 3 to 12 months from idea to a functional robot rolling around. The more complex the robotic solution, the more time it takes. <a href="https://indrorobotics.ca/commander/" target="_blank" rel="noopener noreferrer">InDro Commander</a> can reduce this to 1 to 3 months, depending on the complexity, plus InDro Robotics provides clients with software tutorials and one-on-one support.It’s that hurdle – one faced by pretty much everyone in the robotics R&amp;D world – that led to the creation of InDro Commander.<h2><img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjk1Njc2MjEwMDg5LUNvbW1hbmRlciBvbiBCdW5rZXIuanBnIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 766px;" class="fr-fic fr-dib"></h2><h2>What Does InDro Commander Do?</h2><a href="https://indrorobotics.ca/commander/" target="_blank" rel="noopener noreferrer">InDro Commander</a> is a platform-agnostic module that can bolt on to pretty much any means of locomotion. In the photo above, it’s the box mounted on top of the AgileX bunker (just above the InDro logo). &nbsp;Commander is a single box with critical software and hardware designed to simplify payload integration and enable turn-key tele-operations. &nbsp;Whether you’re adding LiDAR, thermal sensors, RTK, Pan-Tilt-Zoom cameras – or pretty much any other kind of sensor – Commander takes the pain out of integration. &nbsp;With its modular system, reduced development time, software tutorials and one-on-one support, clients can get their robot solution to market faster and with less hassle.The module offers multiple USB inputs for sensors, allowing developers to decide on a mounting location and then simply plug them in. A powerful Jetson EDGE computer handles onboard compute functions. The complete Robot Operating System software libraries (ROS1 and ROS2) are bundled in, allowing developers to quickly access the code needed for various sensors and functions.“Our engineering team came up with the concept of the InDro Commander after integrating and customizing our own robots,” says Philip Reece, CEO of InDro Robotics. “We realized there were hurdles common to all of them – so we designed and produced a solution. Commander vastly simplifies turning a platform into a fully functioning robot.”Account Executive, Luke Corbeth takes it further:“The Commander serves as a “brain-box” for any UGV,” he says. “It safely houses the compute, connectivity, cameras, sensors and other hardware in an IP54 enclosure.”It also comes in several options, depending on the client’s requirements.“There are three ‘standard versions’ which are bundles to either be Compute Ready, Teleoperations Ready or Autonomy Ready,” adds Corbeth.“I’ve realized over time that the value of Commander is our ability to customize it to include, or more importantly, not include specific components depending on the needs of the project and what the client already has available. In reality, most Commanders I sell include some, but not usually all, of what’s in the Commander Navigate. We’re also able to customize to specific needs or payloads.”Below: Commander comes in multiple configurations<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjk1Njc0MDk1MDA2LVNjcmVlbnNob3QtMjAyMy0wOS0xOS1hdC0yLjMzLjQ2LVBNLnBuZy53ZWJwIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 766px;" class="fr-fic fr-dib"><h2>Commander Does The Work</h2>With InDro Commander, developers can spend more time on their actual project or research – and far less time on the build.“For end-users wanting a fully customized robot, Commander saves a huge amount of time and hassle,” says InDro Engineering Lead, Arron Griffiths. “Customers using this module see immediate benefits for sensor integration, and the web-based console for remote operations provides streaming, real-time data. Commander also supports wireless charging, which is a huge bonus for remote operations.”Commander serves as the brains for several InDro ground robots, including Sentinel. This machine was recently put through its paces over 5G in a <a href="https://indrorobotics.ca/putting-sentinel-through-its-paces-at-epri/" target="_blank">test for EPRI</a>, the Electric Power Research Institute.Below: Commander is mounted on Sentinel, a site based autonomous robot, capable of complete continuous monitoring of infrastructure, with the ability to carry out autonomous inspection rounds with thermal, RGB and zoom sensors, for recognition of change detection.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjk1NjczODM5MTAwLVNlbnRpbmVsIEVQUkkuanBnIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" class="fr-fic fr-dii"><h2>5G Operations</h2>Depending on the model, Commander can also serve as a plug &amp; play device for operations over 4G or 5G networks. In fact, InDro was invited by US carrier T-Mobile to a 2022 event in Washington State to demonstrate&nbsp;the live, remote tele-operation of a Sentinel inspection robot.Using a simple Xbox controller plugged into a laptop at T-Mobile HQ in Bellevue WA, we operated a Sentinel in Ottawa – more than 4,000 kilometres away. There was no perceptible lag, and even untrained operators were able to easily control remote operations and cycle between the Pan Tilt Zoom camera, a thermal sensor, and a wide-angle camera used for situational awareness by the operator. Data from all sensors was displayed on the dashboard, with the ability for the operator to easily cycle between them.Below: T-Mobile’s John Saw, Executive Vice President, Advanced &amp; Emerging Technologies, talks about InDro Commander-enabled robots teleoperating over 5G networks&nbsp;<iframe width="640" height="360" src="https://www.youtube.com/embed/-C88iEnsh7E?&amp;wmode=opaque&amp;rel=0&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" frameborder="0" allowfullscreen="" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true">&amp;lt;span class="fr-mk" style="display: none;"&amp;gt;&amp;amp;nbsp;&amp;lt;/span&amp;gt;&amp;amp;lt;span class="fr-mk" style="display: none;"&amp;amp;gt;&amp;amp;amp;nbsp;&amp;amp;lt;/span&amp;amp;gt;&amp;amp;amp;lt;span class="fr-mk" style="display: none;"&amp;amp;amp;gt;&amp;amp;amp;amp;nbsp;&amp;amp;amp;lt;/span&amp;amp;amp;gt;&amp;amp;amp;amp;lt;span class="fr-mk" style="display: none;"&amp;amp;amp;amp;gt;&amp;amp;amp;amp;amp;nbsp;&amp;amp;amp;amp;lt;/span&amp;amp;amp;amp;gt;&amp;amp;amp;amp;amp;lt;span class="fr-mk" style="display: none;"&amp;amp;amp;amp;amp;gt;&amp;amp;amp;amp;amp;amp;nbsp;&amp;amp;amp;amp;amp;lt;/span&amp;amp;amp;amp;amp;gt;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;span class="fr-mk" style="display: none;"&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;nbsp;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;/span&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;span class="fr-mk" style="display: none;"&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;nbsp;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;/span&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;span class="fr-mk" style="display: none;"&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;nbsp;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;/span&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;span class="fr-mk" style="display: none;"&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;nbsp;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;/span&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;span class="fr-mk" style="display: none;"&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;nbsp;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;/span&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;span class="fr-mk" style="display: none;"&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;nbsp;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;/span&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;span class="fr-mk" style="display: none;"&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;nbsp;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;/span&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;span class="fr-mk" style="display: none;"&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;nbsp;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;/span&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;</iframe><h2 id="isPasted">Future-Proof</h2>Platforms change. Needs evolve. New sensors hit the market.With Commander on board, developers don’t need to start from scratch. The modular design enables end-users to seamlessly upgrade platforms down the road by simply unbolting Commander and affixing it to the new set of wheels (or treads).Any sensor, including LiDAR, can be quickly integrated with InDro Commander.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjk1Njc1MDA4NjA2LVNjcmVlbnNob3QgMjAyMy0wOS0yNSBhdCA0LjQ5LjIzIFBNLnBuZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width: 766px;" class="fr-fic fr-dib"> You likely know the saying: “Necessity is the mother of invention.”InDro developed this product because we could see its utility – both for our own R&amp;D, and for clients. We’ve put Commander to use on multiple custom InDro robots, with many more to come. (We have even created a version of this for Enterprise drones.)“On the commercial side, our clients have really benefited from the inherent modularity that the Commander provides,” says Luke Corbeth.“Since the ‘brains’ are separate from the ‘body,’ this simplifies their ability to make the inevitable repairs or upgrades they’ll require. These clients generally care about having a high functioning robot reliably completing a repetitive task, and Commander allows us to operate and program our robots to do this.”It can also save developers money.“On the R&amp;D side, the customizable nature of the Commander means they only purchase what they don’t already have,” adds Corbeth.“For instance, many clients are fortunate enough to have some hardware already available to them whether it’s a special camera, LiDAR or a Jetson so we can support the integration of their existing systems remotely or they can send this hardware directly to us. This cuts down lead times and helps us work within our clients’ budgets as we build towards the dream robot for their project.”Still have questions or want to learn more about Commander?&nbsp;<a href="https://indrorobotics.ca/commander/" target="_blank" rel="noopener noreferrer">Click HERE.</a>

A platform-agnostic module that can bolt on to pretty much any means of locomotion

InDro Commander Streamlines Robotics Research and Development

This article is a chapter from our comprehensive report on 3D printing with wear-resistant plastics. &nbsp;If you're interested in diving deeper and accessing the full report, we invite you to download it below. Gain a holistic understanding and benefit from the complete insights we've gathered. Don't miss out!<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzAxMTg2MzEzNTc0LWV5SmlkV05yWlhRaU9pSjNaWFp2YkhabGNpMXdjbTlxLmpwZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width: 300px;" class="fr-fic fr-dib"> <iframe width="540" height="305" src="https://c8056756.sibforms.com/serve/MUIFAI3PJfiab43rzSudutrE1NSBLWBrIYMuTLjuk7V8EDM15HG0D1C6wjdMHZMiff18ZTqCrBhOkxMaCwPGCk91mWqwuJKESYPi5C21fZjDAFoFa8ZDKmVUuECd05z1jZyX_SNjhMolzGuDIRFD1yvyWVOk7LzkFEgXffPqTznKc-H6-CFw0r9KIcY9W66Oq2bcIK4X1RZRsLl1" frameborder="0" scrolling="auto" allowfullscreen="" style="display: block;margin-left: auto;margin-right: auto;max-width: 100%;" class="fr-draggable"></iframe> <h2 dir="ltr" id="isPasted">High-Performance Thermoplastics</h2>3D printing allows creating and producing complex object geometries from a variety of materials. It has significantly reduced the design-manufacturing cycle, production cost, and material waste. This can be attributed to the fact that 3D printing relies on digital CAD data, which allows for multiple iterations of a product to be produced faster and cheaper than the traditional manufacturing methods. Furthermore, the precise layer-by-layer fabrication process of 3D printing eliminates the need for sculpting the final product and generates minimal residual materials.[1]As technology advances, the variety of materials used in 3D printing has also increased. However, one of the challenges in 3D printing is the need for advanced materials that can match performance and high fabrication standards.[2]&nbsp;Thus, the sector has been focused on developing new high-performance materials that can improve the efficiency and speed of 3D printing and extend its properties and applications. One example is high-performance thermoplastic polymer. It is suitable for 3D printing techniques and supports the production of pieces with high strength-to-weight ratios and properties that can withstand high loads or harsh environments.[3]<h2 dir="ltr">Medical Applications</h2>In medical applications, there are high-performance plastics such as PEI, PEEK and PEKK in use. These are base materials, not optimized for wear and friction. Printable High-performance-thermoplastics including solid lubricants are for example, igus’ iglidur A350 and iglidur RW370. These can be processed on high-temperature FFF printers.The remarkable chemical stability and resistance of high-performance thermoplastic polymers make them well-suited for medical parts, and capable of withstanding autoclave and chemical sterilization processes.&nbsp;Professor Jumpei Arata of Kyushu University in Japan has developed a hand exoskeleton, the RELab tenoexo, using high-performance igus polymers. The exoskeleton is a fully wearable robotic hand orthosis, designed to assist people with sensorimotor hand impairment. Stroke, spinal cord injury, and cerebral palsy are examples of diseases leading to persistent hand impairment.[7]The RELab tenoexo is made up of three components: The exoskeleton comprises a hand module, a wristband sensor, and a backpack. Its design allows for a wide range of daily hand activities and therapy tasks, covering approximately 80% of all grasping activities. It has a maximum fingertip force of 6 N per finger, which makes it capable of easily grasping and lifting many everyday objects, including a half-liter water bottle.[8] <img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjk1NjQyOTg1MTAyLTE2OTU2NDI5ODUxMDIucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" width="650" height="433" id="isPasted" class="fr-fic fr-dii">ReLab's tenoex is lightweight and compact, allowing for ease of use. Image credit: igus&nbsp;<h2 dir="ltr">How does the RELab tenoex work?</h2>The patient wears a wristband and backpack while the hand module is attached to their hand using leather straps. The exoskeleton is portable and compact, able to be used during everyday life. The hand module weighs 148g, and the backpack 720g, ensuring patient comfort.&nbsp;The hand module comprises three thin leaf springs made of stainless steel placed on each other and connected by four plastic links. It provides power, precision, and lateral grasp. Additionally, a Bowden-cable-based force transmission system is attached to the middle spring. When moving forward, the fingers close, and the hand opens when pulled back. <img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjk1NjQyNzc0NzczLTE2OTU2NDI3NzQ3NzMucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" width="650" height="433" class="fr-fic fr-dii">The ReLab tenoex hand exoskeleton actively supports the flexion and extension of the combined index, middle, ring, little finger, and thumb. Image credit: igusWhen the patient moves the hand, the wristband transmits electromyographic (EMG) signals to a microcomputer located in a backpack. If the patient intends to make a grasping movement, the computer detects this and activates the DC motors, allowing motion. The robotic hand orthosis also has an application that allows users to change the force range and closing speed, select between two grasp types, and configure the control system/intention detection strategies. <img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjk1NjQyNzc0OTIwLTE2OTU2NDI3NzQ5MjAucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" width="650" height="433" class="fr-fic fr-dii" style="width: 758px;">The device must be lightweight as well as robust. Image credit: igusHowever, the prototype faced several issues, such as the delicate finger joint structure. These elements keep the leaf springs together and have a lattice-locking mechanism. The first exoskeleton version used a 3D printer with an ABS filament. The manufacturing method and the material were unsuitable for the manufacture of finger joints due to the high friction, resulting in energy loss when the fingers moved. Furthermore, the resolution of a regular 3D printer was not precise enough to recreate the detailed structure of the finger phalanxes.Here comes the application of high-performance thermoplastics for medical purposes. ETHZ University (Eidgenössische Technische Hochschule Zurich) eventually found a solution. With the help of selective laser sintering (SLS) technology and the iglidur i6 high-performance thermoplastic from igus, researchers were able to avoid problems with high friction and low resolution,<a href="https://www.igus.eu/info/3d-print-3d-printing-service" target="_blank" rel="noopener noreferrer">&nbsp;thanks to the igus 3D printing service</a>.[9]<h2 dir="ltr">Properties of iglidur i6</h2>The iglidur i6 high-performance thermoplastic for laser sintering has proven to have an extraordinary greater wear resistance and much lower friction than conventional materials, ensuring longer service life for parts. With abrasion resistance 50 times higher than standard 3D printing materials, it's well-suited for moving applications like the RELab tenoexo. Moreover, the SLS process eliminates the need for tooling, making it suitable for manufacturing special and delicate parts.&nbsp;SLS uses a selective laser that fuses the powder material layer by layer, ensuring some advantages. For instance, unlike FDM printing, there is no need for support structures because the surrounding powder acts as a natural support, avoiding the need for post-processing. Moreover, it guarantees uniform distribution of material and good interlayer bonding, which leads to consistent mechanical properties. The unique material properties of iglidur i6 also make it ideal for creating 3D-printed finger phalanxes in an exoskeleton.[10]<h3 dir="ltr">Reducing friction</h3>The self-lubricating SLS material iglidur i6 had been specially developed for manufacturing parts subject to friction and was used successfully for manufacturing the finger joints. 3D printed finger phalanges made of high-performance iglidur i6 polymer ensure optimum force transmission. This material is ideal for moving applications and contains solid lubricants, making it easy to handle without needing additional lubrication. This feature makes it suitable for therapeutic applications.<h3 dir="ltr">Delicate parts</h3>Laser sintering as a manufacturing method is ideally suited for replicating complex geometries, filigree structures, and delicate details. This makes it possible to manufacture small volumes and one-off components cost-effectively. iglidur i6 was initially developed to manufacture worm wheels for robot joints and wear parts in general.<h3 dir="ltr">Resistance</h3>One of the most outstanding features of iglidur i6 is its resilience and abrasion resistance. A sintered gear made of this abrasion-resistant iglidur plastic was tested under the same conditions as a machined gear made of POM for two months. The gear made of POM exhibited signs of severe wear after 321,000 cycles and failed after 621,000 cycles. In contrast, the gear made of iglidur i6 continued to function after 1 million cycles, with only minor signs of wear. &nbsp;<h3 dir="ltr">Light&nbsp;</h3>The iglidur i6 is an impressively lightweight material, making it ideal for applications where weight is a key factor. For instance, it is a perfect choice for a hand orthosis that needs to be worn for long periods. It is worth noting that the hand module, which features finger joints made of iglidur i6, only weighs 148g.&nbsp;<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzAxMTg2OTE4MTY1LWltYWdlLmltYWdlZm9ybWF0LjEyODYuNDc2NzkwNjA2ICgxKS5qcGciLCJlZGl0cyI6eyJyZXNpemUiOnsid2lkdGgiOjk1MCwiZml0IjoiY292ZXIifX19" style="width: 300px;" class="fr-fic fr-dib">The Relab tenoex allows users to change the force range and closing speed, select between two grasp types, and configure the control system/intention detection strategies. Image credit: RELAB ETHZ There are more current benefits of the application of high-performance thermoplastics. With the help of SLS technology and iglidur i6 high-performance plastic, it is now possible to produce delicate structures of finger joints without the need for support structures. This also eliminates the need for post-processing. For example, pieces from FDM 3D prints tend to have a slightly rough surface, suggesting the need to smooth out the imperfections through sanding.[11]&nbsp;Moreover, RELab tenoexo exoskeletons are individually adapted to fit individual patients. The company developed an algorithm that adjusted the digital model of the exoskeleton to the size of the patient's hand with just a few clicks, thereby avoiding any mistakes. This means the exoskeleton can be manufactured to meet individual customer requirements quickly and without complications.In addition, with the help of an online 3D printing service tool, ETHZ scientists can order the required parts in just a few minutes. The manufacturing process is usually completed overnight, and the finished finger joints can be fitted after just a few days.This is the only manufacturing method that approaches the speed and cost-effectiveness of 3D printing where a customized small-volume manufacturer is concerned. The adaptable and fast production characteristics of this method are game changers, especially considering that conventional customization methods are complex due to molding or other tool-based methods.<h2 dir="ltr">Conclusion</h2>High-performance thermoplastics and SLS have exceptional properties, such as being friction-free, allowing for detailed and precise printing, being self-lubricating, lightweight, and easy to produce. By combining these materials, users can better support their daily activities and receive rehabilitation training.&nbsp;This article was co-authored by Ana Carla Sorgato.<hr><h2>The Engineer’s Guide to 3D Printing with Wear-Resistant Plastic Materials</h2>Explore the transformative world of 3D printing as we delve into the intricacies of using wear-resistant plastic materials. <a href="https://www.wevolver.com/article/the-engineers-guide-to-3d-printing-with-wear-resistant-plastic-materials/draft" target="_blank" rel="noopener noreferrer">This guide</a> offers engineers a comprehensive overview of material properties, applications, and best practices. Unlock the potential of durable plastics and revolutionize your manufacturing processes.<h3><img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjk5NjIyODA5OTIyLU1pdHN1YmlzaGkgQ2hlbWljYWwgR3JvdXAgIEdyb3d0aCBHYXJhZ2UgIE9wZW4gSW5ub3ZhdGlvbiBQcm9ncmFtICg2OTQgeCA0MzIgcHgpICg5MDEgeCA1NjEgcHgpICgyKS5wbmciLCJlZGl0cyI6eyJyZXNpemUiOnsid2lkdGgiOjk1MCwiZml0IjoiY292ZXIifX19" style="width: 300px;" class="fr-fic fr-dib"></h3><iframe width="540" height="305" src="https://c8056756.sibforms.com/serve/MUIFAI3PJfiab43rzSudutrE1NSBLWBrIYMuTLjuk7V8EDM15HG0D1C6wjdMHZMiff18ZTqCrBhOkxMaCwPGCk91mWqwuJKESYPi5C21fZjDAFoFa8ZDKmVUuECd05z1jZyX_SNjhMolzGuDIRFD1yvyWVOk7LzkFEgXffPqTznKc-H6-CFw0r9KIcY9W66Oq2bcIK4X1RZRsLl1" frameborder="0" scrolling="auto" allowfullscreen="" style="display: block;margin-left: auto;margin-right: auto;max-width: 100%;" class="fr-draggable">&nbsp;</iframe><h2 dir="ltr"> </h2><h2 dir="ltr">References</h2><ol><li dir="ltr">Azom. “https://www.azom.com/article.aspx?ArticleID=20017”</li><li dir="ltr">Valino, A. D., Dizon, J. R. C., Espera Jr, A. H., Chen, Q., Messman, J., &amp; Advincula, R. C., 2019. “<a href="https://www.sciencedirect.com/science/article/pii/S0079670018303976" target="_blank">https://www.sciencedirect.com/science/article/pii/S0079670018303976</a>”</li><li dir="ltr">Anniwaa “<a href="https://www.aniwaa.com/insight/am-materials/am-thermoplastics-breakdown-by-performance/" target="_blank">https://www.aniwaa.com/insight/am-materials/am-thermoplastics-breakdown-by-performance/</a>”</li><li dir="ltr">Wevolver. “https://www.wevolver.com/article/peek-3d-printing-unlocking-the-potential-of-high-performance-polymers”</li><li dir="ltr">Algarni, Mohammed; Ghazali, Sami., 2021. “<a href="https://www.proquest.com/docview/2565095716" target="_blank">https://www.proquest.com/docview/2565095716</a>”</li><li dir="ltr">Bond 3D. “<a href="https://www.bond3d.com/market/peek-medical/" target="_blank">https://www.bond3d.com/market/peek-medical/</a>”</li><li dir="ltr">ETH Zurich. "<a href="https://relab.ethz.ch/research/current-research-projects/Robotic%2520Hand%2520Orthosis%2520.html" target="_blank">https://relab.ethz.ch/research/current-research-projects/Robotic%20Hand%20Orthosis%20.html</a>”</li><li dir="ltr">Tobias Bützer, Olivier Lambercy, Jumpei Arata, and Roger Gassert (2021). “<a href="https://www.liebertpub.com/doi/abs/10.1089/soro.2019.0135" target="_blank">https://www.liebertpub.com/doi/abs/10.1089/soro.2019.0135</a>”</li><li dir="ltr">3dnatives. 2021. “<a href="https://www.3dnatives.com/en/3d-printed-finger-joints-igus-110120204/" target="_blank">https://www.3dnatives.com/en/3d-printed-finger-joints-igus-110120204/#</a>”</li><li dir="ltr">Igus. “<a href="https://www.igus.eu/info/3d-printing-application-exoskeleton" target="_blank">https://www.igus.eu/info/3d-printing-application-exoskeleton</a>”</li><li dir="ltr">All3dp “<a href="https://all3dp.com/2/fdm-3d-printing-post-processing-an-overview-for-beginners/" target="_blank">https://all3dp.com/2/fdm-3d-printing-post-processing-an-overview-for-beginners/</a>”</li></ol>

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