Celera Motion, a business unit of Novanta Inc., launched its Summit Designer tool that delivers standard market-ready printed circuit board (PCB) designs for robotic applications.

Celera Motion, headquartered in Bedford, Mass., is a provider of motion-control components and subsystems for OEMs serving a variety of medical and advanced industrial markets. Celera Motion said it offers precision encoders, motors and customized mechatronic solutions. Celera Motion will be exhibiting in booth 335 of the Robotics Summit & Expo, the world’s premier commercial robotics development event that takes place May 10-11 in Boston.

Summit Designer is an open-source PCB design library featuring a diverse and vast offering of market-ready application-specific PCBs that are designed, supported and updated by experts. It is a new way to develop compact robot joints, multi-axis mobile robotics systems, industrial end-effectors and surgical robots, among many others.

“Summit Designer allows developers to create an ideal application using tested and proven PCB Designs,” said Marc Vila, director of strategy and business development, Celera Motion. “This ingenious new platform cuts development time, decreases the chances of error and reduces prototype iterations. That’s more important than ever as markets evolve faster and grow more competitive. Unexpected delays can be catastrophic to projects.”

According to Celera Motion, every design is open-source and consists of a fully customizable and fully documented Altium project. Users only have to choose and add their desired modules to create a fully functional servo drive design for a market-ready robot. The options are designed to satisfy the most common requirements, such as
type of connectors, communication protocols, safety functions and motor and encoder specifications. Users then receive a fully scalable and modular download file, ready to edit at their convenience. Experts are available to answer questions and guide users.

Celera Motion said the entire process takes five steps:

• 1. Bring an idea for a new motion control application to the Summit Designer website
• 2. Check the PCB designs there to find the one that fits your needs
• 3. Customize it with our in-depth application guide
• 4. Talk to our experts and get support whenever needed
• 5. Plug into a Summit Drive and go to market

“Summit Designer was developed by top experts in motion control applications and robotics,” Vila said. “Our goal was to make the process as simple, flexible and seamless as possible. Each project allows for high customization and provides all the necessary tools in a single download.”

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Boston Dynamics never disappoints when it releases a video showing new capabilities for its robots. And it just released a video, “Atlas Gets a Grip,” in which the humanoid performs a slew of new moves at a simulated construction site.

A “construction worker” atop a scaffold conveniently forgot some tools down on the ground. Instead of hopping down to get the tools himself, Atlas brings the tools to him. And this is where the magic happens.

Atlas, using a claw gripper, picks up and manipulates a wooden plank to create a bridge for itself onto the scaffold. It then picks up a toolbag, runs onto the scaffold, spins around and throws the toolbag up to the construction worker. Atlas then pushes a wooden box off the scaffold and flips and twists its way to the ground.

You can watch the video atop this page. Boston Dynamics said the new capabilities represent a natural progression of the humanoid robot’s skillset, particularly in areas of perception, manipulation and autonomy. Atlas’ ability to pick up and move objects of different sizes, materials, and weights while staying balanced is enabled by improved locomotion and sensing capabilities.

For this video, Boston Dynamics installed utility “claw” grippers with one fixed finger and one moving finger. Boston Dynamics said this gripper debuted during its Super Bowl commercial when Atlas lifted a keg over its head. These simple grippers are designed for heavy lifting tasks.

According to Boston Dynamics, some of the other new capabilities include:

• Improved control systems in order to jump 180-degree jump while holding the wooden plank.
• Performing a spinning jump while throwing the tool bag. To accomplish this task, Boston Dynamics extended the model predictive controller (MPC) to consider the coupled motion of both the robot and object together.
• Pushing the wooden box from the platform, which meant Atlas needed to generate enough power to cause the box to fall without sending itself off of the platform.
• Atlas’ concluding move, an inverted 540-degree, multi-axis flip, adds asymmetry to the robot’s movement making it a much more difficult skill than previously performed parkour.

“We’re layering on new capabilities,” said Ben Stephens, Atlas controls lead, Boston Dynamics. “Parkour and dancing were interesting examples of pretty extreme locomotion, and now we’re trying to build upon that research to also do meaningful manipulation. It’s important to us that the robot can perform these tasks with a certain amount of human speed. People are very good at these tasks, so that has required some pretty big upgrades to the control software.”

Boston Dynamics released a must-watch video (below) that takes you behind the scenes of how this new routine was developed.

In a blog, Boston Dynamics explained some of the more complex sequences in the new routine. Stephens said Atlas manipulating the large wooden plank was especially challenging. Instead of turning around cautiously, Atlas performed a 180-degree jump while holding the plank. Stephens said this meant Atlas’ control system needed to account for the plank’s momentum to avoid toppling over.

He also said pushing the wooden box from the platform is a deceptively complex task. Atlas needed to generate enough force to cause the box to fall, leaning its weight into the shove without sending its own body off the platform.

Stephens also said the flip at the end of the routine is much more difficult than previous acrobatics. The twist adds asymmetry that doesn’t exist in a regular backflip. Not only is the math more complicated, but in trial runs, Atlas kept getting tangled in its own limbs as it tucked its arms and legs.

“We’re using all of the strength available in almost every single joint on the robot,” Deits says. “That trick is right at the limit of what the robot can do.”

Stephens said humanoids that can routinely tackle dirty and dangerous jobs in the real world are a “long way off.” So it appears Atlas will remain a research platform for the foreseeable future.

“Manipulation is a broad category, and we still have a lot of work to do,” he said. “But this gives a sneak peek at where the field is going. This is the future of robotics.”

The post Watch Boston Dynamics’ Atlas humanoid work at a ‘construction site’ appeared first on The Robot Report.

What if you could design and build a surgical robot that helps doctors perform less invasive, more precise operations and achieve better patient outcomes? While the results of any surgery depend on the challenges of the specific case and the skill of the surgeon, better tools support better care.

Here’s how next-generation motion engineering can help you develop the next generation of surgical robots.

Place the arms as close together as possible

Conventional surgical robots include large columns with multiple arms holding a tiny camera and various instruments such as scissors, graspers, needle holders, clip applicators and more. Depending on the surgery, the ideal procedure is performed through a single, small incision that must simultaneously accommodate the visualization camera and any needed instruments.

If you ask any surgeon, they will tell you the ideal angle of approach for the camera and instruments into the incision site is as parallel and close together as possible—both to minimize trauma and to eliminate any discrepancy between the camera view and the angle at which each instrument operates.

Achieving an identical angle of approach is, of course, impossible, as the instruments can’t occupy the same space. Today’s instruments are very thin and compact, however. It’s the single-column, multiple-arm design of conventional surgical robots—plus the sheer bulk of their arm joints—that limits the angle of approach when multiple instruments are deployed. This is the main challenge to overcome when designing the next generation of robots.

Minimize the axial length of arm joints

Standalone arms provide much greater flexibility in positioning compared to the conventional design, allowing multiple arms to be aligned in a plane much closer to parallel. To further approach the parallel ideal, the bulk of each arm must be minimized.

The limiting factor for how closely together the arms can operate is the axial length of the arm joints. You need a motor and gearing system that delivers all the required torque with the shortest possible axial length. Every millimeter saved without compromising performance helps surgeons work more effectively and creates an important market advantage for your surgical robot.

Start with the gearing

High-torque motors with short stack lengths are key to achieving optimum torque while minimizing axial length, total volume and weight. However, beyond the stack length of the motor itself, the gearing and feedback devices also need to be tightly integrated within the joint.

Ultimately, it’s the gearing that translates the relatively high-speed motion of the motor into the lower speed and higher torque needed to move the load of the robotic arm at the optimum speed, precisely position it, and hold the load steadily in place. Because the selection of gearing also impacts the axial length of the joint, this is the place to start in creating your design.

The required speed, performance and load points will determine the appropriate gear set. No matter what ratio is required, this application calls for strain wave technology, also known as “harmonic” gearing.

Strain wave gearing provides three indispensable advantages:

• 1. It enables the most compact axial integration within the joint.
• 2. It offers relatively high gear ratios—typically ranging from a gear reduction of 30:1 to 320:1—to accelerate/decelerate loads smoothly and position them precisely.
• 3. It operates with zero backlash to minimize any unwanted movement that could potentially affect the precision of the procedure or induce unnecessary trauma.

Match the motor to the gearing and thermal requirements

Having specified the appropriate gear technology and ratio, you can select a motor based on the gear ratio, the speed at which the arm must run, and the mass it needs to hold. Thermal rise when operating at typical or maximum load can also be an important consideration, as excessive heat in the tight confines of the joint can damage gearing lubricant, encoder electronics and other components in close proximity. A motor that can deliver full performance at a lower thermal rise is desirable.

Take advantage of the D2L rule

As part of your motor specification process, you can further reduce axial length through an often-overlooked principle of motor design referred to as the D2L rule.

In robotic joint design, the diameter of the motor is typically of minor concern. To enable robotic arms to operate as closely together as possible, you instead need to minimize the axial length. The D2L rule allows you to trade off a larger diameter for a significantly reduced axial length. Here’s how it works.

In the frameless motors used in robotic joints, torque increases or decreases in direct proportion to changes in motor length, but as the square of changes in the moment arm of the motor. In other words, under the D2L rule, doubling the moment arm—and thereby approximately doubling the overall diameter—produces a fourfold increase in torque.

Or, more relevant to surgical robot design, doubling the moment arm allows you to reduce the stack height by a factor of four while maintaining the same torque. This is a huge advantage when your design priority is to achieve the most compact axial length.

For next-generation surgical robot performance, choose next-generation motors specially designed for robotic applications. This will help you accelerate your development time and deliver surgical robots that allow doctors to operate instruments as close together and as close to parallel as possible.

Better tools mean better healthcare and a healthier surgical robotics business.

The post How motion engineering helps develop next-gen surgical robots appeared first on The Robot Report.

Mobile robotics is a high-growth market both in and outside the logistics sector. Tune in to learn how Novanta simplifies the application development process.

In this context, time-to-market becomes crucial, as well as minimizing the development costs to offer a more competitive and affordable solution to end customers and OEMs. However, these robots are complex multi-component machines, with a high level of integration and tough certification requirements that often cause the design phase to extend endlessly.

Novanta Drives (formerly Ingenia Motion Control) is a product line with more than 15 years of experience in the design of state-of-the-art miniature servo drives for robotics and EV applications. In this webinar, we are pleased to present a series of open-source solutions and resources intended to dramatically minimize the engineering effort in developing most logistic robots.

Drive miniaturization, high efficiency, power density, proper EMC practices, and the sharpest motion control are offered by Novanta Drives as a game of building blocks to easily customize a fully integrated solution, thus simplifying and even completely avoiding most of the typical issues and setbacks that come with developing a logistics robot.

Attendees of this webinar will learn:

• Competitive market analysis for logistics robotics.
• The need for a centralized topology with multi-purpose architecture.
• Removing the development’s complexity – Novanta’s open-source solution.

Date/Time: Thursday, January 19, 2023 at 11:30 AM EST

Sponsored by:

Speaker

Ignacio Pedrosa has been a hardware designer at Novanta for the last 8 years and now is tapping into the applications field. He has expertise in power electronics, design for manufacturing, EMC, and motion control and is eager to invest in the fields of robotics and automation.

Direct collaboration with top surgical, industrial, and collaborative robot manufacturers, as well as brilliant engineers in a number of fields and industries associated with motion control and servo drives, has allowed him to build up a valuable perspective on these technologies that he always pleased to share.

The post Webinar: motion control in logistics robotics made easy appeared first on The Robot Report.

The setup for NVIDIA’s DeXtreme project using a Kuka robotic arm and an Allegro Hand. | Source: NVIDIA

Robotic hands are notoriously complex and difficult to control. The human hands they imitate consist of 27 different bones, 27 joints and 34 muscles, all working together to help us perform our daily tasks. Translating this process into robotics is more challenging than developing robots that use legs to walk, for example. 

Methods typically used to teach robot control, like traditional methods with precisely pre-programmed grasps and motions or deep reinforcement learning (RL) techniques, fall short when it comes to operating a robotic hand. 

Pre-programmed motions are too limited for the generalized tasks a robotic hand would ideally be able to perform, and deep RL techniques that train neural networks to control robot joints require millions, or billions, of real-world samples to learn from.  

NVIDIA, instead, used its Isaac Gym RL robotics simulator to train an Allegro Hand, a lightweight, anthropomorphic robotic hand with three off-the-shelf cameras attached, as part of its DeXtreme project. The Isaac simulator is able to run more than simulations 10,000 times faster than the real world, according to the company, while still obeying the laws of physics. 

With Isaac Gym, NVIDIA was able to teach the Allegro Hand to manipulate a cube and match provided target positions, orientations or poses. NVIDIA’s neural network brain learned to do all of this in simulation and then the team transplanted it to control a robot in the real world. 

Training the neural network

In addition to its end-to-end simulation environment Isaac Gym, NVIDIA used its PhysX simulator, which simulates the world on the GPU that stays in the GPU memory while the deep learning control policy network is being trained, to train the hand. 

Training in simulations provides a number of benefits for robotics. Besides NVIDIA’s ability to run simulations much faster than they would play out in the real world, robot hardware is prone to breaking after a lot of use. 

According to NVIDIA, the team working with the hand often had to stop to repair the robotic hand, things like tightening screws, replacing ribbon cables and resting the hand to let it cool, after prolonged use. This makes it difficult to get the kind of training the robot needs in the real world. 

To train the robot’s neural network, NVIDIA’s Omniverse Replicator generated around five million frames of synthetic data, meaning NVIDIA’s team didn’t have to use any real images. With NVIDIA’s training method, a neural network is trained using a technique called domain randomization, which changes lighting and camera positions to give the network more robust capabilities. 

All of the training was done on a single Omniverse OVX server, and the system can teach a good policy in about 32 hours. According to NVIDIA, it would take a robot 42 years to get the same experience in the real world. 

The post NVIDIA teaches dexterity to a robot hand appeared first on The Robot Report.

Micropsi Industries announced its software, MIRAI, is now compatible with numerous robots from FANUC, a leading supplier of robotics and factory automation. With MIRAI, FANUC customers can add hand-eye coordination to multiple FANUC industrial and collaborative robots (cobots) to handle functions such as cable plugging and assembly.

The MIRAI controller generates robot movements directly and in real time. Robot skills are trained, not programmed, in a few days through human demonstration, without requiring knowledge of programming. To train a robot, a human repeatedly demonstrates a task by manually guiding the robot by the robot’s wrist. The recorded movements are then transformed into a skill.

Cable plugging applications such as flat ribbon cables for the electronics industry or industrial automotive connectors typically require a high degree of flexibility to accommodate shape instability, making it a difficult task for any robot.

“Grabbing a flexible part, guiding it and placing it accurately into a socket may be a trivial task for humans, but it has been basically impossible to complete for industrial robots,” said Prof. Dominik Bösl, chief technology officer, Micropsi Industries. “That’s because while robots can work tirelessly and precisely with high repeatability, they are limited in their ability to perform complex motorized processes. The required hand-eye coordination is just not present in a robot. If the robot falters due to variances or deviations, employees must intervene, and are sometimes burdened with unergonomic tasks. This inhibits the performance of manufacturing companies who are already struggling with the prevailing shortage of skilled workers.”

Micropsi Industries plans additional automation projects that will expand the range of applications for FANUC’s industrial robots. The medium- and long-term goal: to revolutionize industrial work from the ground up.

“Micropsi Industries working with FANUC’s robots will break new ground by making automation possible where it has never been before,” Bösl added. “In this strategic relationship, our MIRAI intelligent controller meets the world’s largest portfolio of industrial robots. Together, we are tapping into the nearly unlimited possibilities of task-specific machine learning for robotics. In doing so, we are making it accessible to even more industries and users, ensuring greater flexibility under real production conditions.”

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Robotics Engineering Week, produced by The Robot Report and WTWH Media, kicks off on Tuesday, November 8, 2022. Those interested in attending can still register for the all sessions for the event. 

Despite the monumental potential of new robotics-enabling technology and substantial social and business drivers, the pace of development for new robotics technologies, products and services has been painfully slow.

The complexity of developing robotics systems, together with the unending crush of technological innovation, has hampered innovation and slowed robotics product releases. This, in turn, has placed companies – both start-ups and mature firms – at risk.

The webinar is a digital event series featuring keynotes and panels designed to deliver the information and guidance engineers, technical managers, business development professionals, researchers and more need to build the next generation of commercial robotics systems more quickly and easily. 

The complete agenda for RoboBusiness is below, and the full conference is here. 

Tuesday, Nov. 8

Session: Intelligent Sensing for Object Recognition, Manipulation and Control
Brual Shah, Co-Founder and CTO, GrayMatter Robotics, and Jeff Mahler, Co-founder and CTO, Ambi Robotics
11:00 AM ET

Grasping and manipulation, the ability to directly and physically interact with and modify objects in the environment, is perhaps the greatest differentiator between robotic systems and all other classes of automated systems. Many types of robots make use of advanced sensing solutions – from tactile, to vision, proprioceptive, and more – to identify, pick up and operate on all manner of objects, with goals ranging from providing human-like dexterity and autonomous manipulation, to high precision repeatability, and on to superhuman strength and endurance. During this Robotics Engineering session, attendees will learn of the latest sensing technologies and techniques commercially available to support object recognition, grasping, manipulation and control, as well as solutions emerging from the lab that will allow for whole new classes of robotics applications.

Session: Using Simulation for the Design and Development of Robotics Systems
Erin Rapacki-Bishop, Senior PMM Robotics & Isaac Sim, NVIDIA
2:00 PM ET

The development of robots and robotic technology requires the mastery of multiple disciplines – primarily software development, mechanical and electrical engineering.  Robotics development is made even more difficult as it is limited by embedded and real-time constraints. Commercial viability adds additional burdens for the robotics developer. Solution providers have responded to these difficulties by providing a whole host of robotics design, development tools, simulation and testing tools, as well as ready-made robotic ‘platforms’, that dramatically simplifies the job of designing, developing, testing and manufacturing robots and robotic products. This Robotics Engineering Week session will provide an overview of current robotics development solutions, as well as highlight development trends.

Wednesday, Nov. 9

Session: Grounding Your Cloud-based Robotics Initiatives for Success
Andrei Kholodni, Principal Technologist, Wind River, and Brian Gerkey, CEO/Cofounder, Open Robotics
11:00 AM ET

Machine learning (and deep learning) technologies and techniques have found great success in enabling advanced robotics capabilities such as decision-making, object identification, vision processing, autonomous navigation, motor control, sensor integration and other functions, as well as speech, facial and emotion recognition. Moreover, robotics designers and engineers can also take advantage of different types of distributed execution architectures – edge, fog and cloud – to optimize their systems and their intended applications. While the large number and variety of machine learning alternatives for robotics development and deployment is beneficial, they can also result in confusion and indecision, particularly given the rapid rate of technological innovation and product introduction. In this Robotics Engineering Week session, designed to provide some much-needed clarity, attendees will learn how the latest AI and machine learning technologies and techniques can be employed in ground-based, aerial and maritime systems to make robots more intelligent and functional. 

Session: Advanced Motion Control Solutions for Robotics Systems
Brian Coyne, VP of Engineering, Harmonic Drive LLC
2:00 PM ET

‘Motion’ in the physical world, whether in the form of changing place, position or posture, is perhaps the greatest differentiator between robotic systems and all other classes of engineered products. It is motion is that makes robotics systems ‘robotic’, and it is advances in motion control technologies that have spurred robotics innovation, with the result that there has been a dramatic increase in the use of robotics technologies and products around the globe. In this Robotics Engineering Week session, attendees will learn how support for robotic motion control has improved with the introduction of new products and technologies, and how they allow for new capabilities, new applications, and entry into new markets. Case studies and product examples will be used to highlight salient points. 

Thursday, Nov. 10

Session: Intelligent Vision and Sensing Solutions for Autonomous Mapping and Navigation
Paul Baim, VP Product Management & Systems Engineering, DreamVu Inc
11:00 AM ET

Commercial robotic systems typically require multiple types of sensors to capture information about the physical world, which following fusion and further processing allows them localize themselves, navigate while avoiding obstacles, and provide additional information. The number, type, and quality of the onboard sensors vary depending on the price and target application for the platform. Common sensor types include 2D / 3D imaging sensors (cameras), 1D and 2D laser rangefinders, 2D and 3D sonar sensors, 3D High Definition LiDAR, accelerometers, GPS and more. Thankfully, solution providers continue to release low-cost, increasingly powerful products, and new sensing technologies are always emerging. In this Robotics Engineering Week session, attendees will learn of the latest advances in sensing products and technologies, including use cases highlighting important trends and examples of the latest sensing trends and techniques.

Session: Motion Control for Healthcare Robotics Applications: Functional Requirements, Critical Capabilities
Prabh Gowrisankaran, VP of Engineering & Strategy, Performance Motion Devices
2:00 PM

Healthcare robotics share many areas of technical commonality with electrically powered medical devices, as well as the common goal of improving patient care. A key difference, however, is that for all robotics systems, motion and movement in the physical world is expected. For robots, motion (and motion control) is presumed and definitional. As such, motion control technologies and techniques are central considerations for any robotics engineering initiative. Compared to industrial and consumer motion control technologies, motion control solutions for healthcare applications typically have different, and often very stringent, functional requirements in areas such as safety, reliability, tolerances, cleanability, sterilization and more. In this Robotics Engineering Week session, attendees will learn about the leading functional requirements and critical capabilities of motion control solutions for healthcare robotics applications.

The post Robotics Engineering Week to address critical development issues appeared first on The Robot Report.

Celera Motion, a business unit of Novanta, recently introduced its Everest S servo drive. The company said it’s about 30% smaller than its predecessor and that the EtherCAT and CANopen versions deliver bus latency reduced to 1 cycle.

Designed with 3 kW of power and a starting weight of just 18 grams, the Everest S is designed for applications such as surgical robots, exoskeletons, collaborative robots, legged robots and autonomous mobile robots.

The Everest S includes all the features of other Everest servo drives plus Dual BiSS-C feedback support. Celera Motion said it combines 16-bit differential current and four configurable ranges.

“We’re excited to introduce the Everest S to meet the growing demand for smaller, faster servo drives that provide more space for applications and even better performance,” said Marc Vila, Director of Strategy & Business Development for Celera Motion. “Our goal is to give product designers as much freedom and flexibility as possible, and the Everest S delivers that and more.”

Celera Motion said the Everest S offers:

• An optimized hardware architecture that allows for high-speed communication protocols with minimum latency
• A current loop running at 50 kHz and a velocity loop at 25 kHz
• An ultra-compact design with a low profile and a lightweight design
• Multiple integration options and power management
• Its latest motion-control software with a user-friendly configuration wizard and diagnostics

Celera Motion said high-speed SPI bus communication is available for optimized EtherCAT/CANopen multi-axis architectures. Everest S also has been designed to meet industrial functional safety standards to ensure continuous safe operation.

Everest S is the latest version of Summit Servo Drives Series. Others include the Capitan Series and the Denali Series.

In 2021, Novanta acquired acquiring Schneider Electric Motion USA for $115 million and ATI Industrial Automation for $172 million. After officially acquiring Schneider Electric Motion, Novanta renamed the company Novanta IMS.

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Two Kawasaki welding robots coordinate their motions using RealTime Robotics’ RapidPlan software. | Credit: RealTime Robotics

Realtime Robotics, a Boston-based developer of collision-free, autonomous motion planning for industrial robots, has raised another $14.4 million in funding. The funding was led by Soundproof Ventures, Heroic Ventures and SIP Global Partners and brings the company’s total funding to date to more than $60 million.

The funding comes on the heels of the official launch of Realtime’s RapidPlan software, which helps manufacturers design and deploy industrial automation. With RapidPlan, customers can automate the programming, deployment and control of their industrial robots within applications such as automotive or logistics. The software can autonomously create and choreograph all robot movements without the need for brand-specific robot programming.

Within RapidPlan’s software environment, users create a digital twin simulation of their workcell and then point and click on robots and target points to visualize collision-free task plans. The same software used for the simulation environment controls real-world robots.

“We have seen a tremendous industry response to the launch of RapidPlan and its ability to make collision-free operations a reality for industrial robotics, speeding programming time and increasing throughput,” said Peter Howard, CEO of Realtime Robotics. “We’ve recently pivoted away from hardware to pure software, making it even easier for all customers and partners to integrate our revolutionary technology within their existing stack and workflows. This latest round of funding will assist us in scaling to meet demand.”

Realtime Robotics said it will use the new funding to continue to scale. It will also be used to invest in overall engineering development and to enable additional enhancements to its core software.

“As supply chains are increasingly taxed, industry craves efficiency,” added Michael Silverstein, Managing Partner of Soundproof Ventures. “By automating the most challenging and costly aspects of operating industrial robots, Realtime Robotics enables customers to unlock the promise of automation and drive output well beyond what has ever been conceived.”

Realtime Robotics is a former resident startup of MassRobotics. It moved out in 2019 after it grew to 30-plus employees. You can read more about the founding of Realtime Robotics in this profile written by MIT.

The post Realtime Robotics raises $14.4M for motion planning software appeared first on The Robot Report.

Nikon announced the expansion of its C3 eMotion intelligent actuator unit lineup, each of which combines vital robot joint components including a motor, speed reducer, motor driver, brake and encoders together into one package. Nikon will now offer the IAU-30 and IAU-300 types, which differ in terms of size, torque and other characteristics.

The C3 eMotion is a robotic joint unit for collaborative robot arms that facilitates easier building of robots even by users who have no knowledge of robot design. Moreover, thanks to its high versatility, the C3 eMotion can also be used as a component in semiconductor equipment, machine tools, measurement instrument, conveyance equipment and other machines and systems which require high stopping accuracy, machining precision or similar.

The C3 eMotion operates under Nikon’s proprietary double-encoder structure (containing two encoders), which enables detection of external forces and robot operation stoppage in response, direct teaching in which the robot can be made to learn commands via direct manipulation by human users, and a wide range of other useful functions.

Many manufacturers face labor shortages and as they need to implement production facility automation and labor-saving in response, there is an increasing demand for robots that can work cooperatively alongside humans. However, because robots comprise a wide array of components such as motors, speed reducer, motor driver, brake and encoders, sophisticated skills and know-how are required to coordinate all of these. With the C3 eMotion, Nikon combines all of these parts into a single-package robotic joint unit which can be used together with a robotic arm to form a robotic joint structure.

In addition to the IAU-60 and IAU-200 units released in 2020, Nikon has added the new IAU-30, which is compact type and IAU-300 which is larger-hollow and larger-torque type. These additions to C3 eMotion lineup give customers a wider range of options, enabling freer robotic system creation tailored to specific user needs. Moving forward, the company will continue developing new models and expanding this lineup in order to better address market demand.

Main Features

1. Contributing to more flexible and easier robot design

Combining a C3 eMotion unit with a robotic arm selected based on intended usage application enables easy changes to robotic joint numbers, maximum load capacity and other factors, thus facilitating more flexible and easier robot design.

2. High safety performance

The double-encoder structure utilizing encoders in two locations at both the input shaft and output shaft enables detection of even minor external forces applied during robot operation. For example, if a human worker or object comes into contact with the robot while it is working, the robot can detect the impact (external force) and safely stop operations.

3. Operations with direct teaching

The double-encoder structure enables responses to detected external forces, it is possible for human operators to directly manipulate the robot and thus program operations through the direct teaching.

4. High-precision positioning performance

Because high performance encoders installed on both the input shaft and the output shaft via the double-encoder structure make it possible to monitor rotation speeds on both shaft and positioning information with high accuracy. This enables high-precision positioning performance, which is vital for collaborative operations between human workers and robots.

The post Nikon adds 2 actuators to C3 eMotion lineup appeared first on The Robot Report.

In the automation world, there can be a fine line between what is considered a motion controller and what represents a basic servo drive. It is critical to understand the functionality and intelligence of each device since, in many applications, both a motion controller and a servo drive are required to complete the system.

The servo system

A servo motor is powered by a servo drive that supplies voltage and current to the motor coils and then monitors feedback to close the servo loop. In most cases, the servo drive consists of three embedded servo loops – the current (or torque) loop, velocity loop, and position loop – that interact with each other to create precision motion. The expected motor operation will determine which loops are required.

• In a torque control application, which requires a specific torque, only a current loop is needed. Since torque is directly proportional to current, torque is regulated by a sensor that provides current feedback to the servo drive.
• With velocity control applications, it is common to find both current and velocity loops. The velocity loop monitors a sensor that provides velocity information to the servo drive and then uses this data to adjust the current loop to increase or decrease torque.
• Finally, a position loop application employs a feedback sensor coupled to the motor that sends position information to the servo drive or motion controller, which in turn signals the velocity loop to increase or decrease velocity, which then relays the information to the current loop to regulate torque.

Defining the drive and controller roles

In a torque control application of a brushless dc servo motor, a “device” supplies current and voltage to a motor based on a commanded input measured against the current feedback. The apparatus that provides the power to the motor is called, in proper terms, a servo amplifier or servo drive. A current or torque drive is useless unless it receives a specific command to tell it what torque to produce. The command can come from a variety of sources that essentially act as the “controller”. The command may be as simple as a person, functioning as a controller, manually adjusting a potentiometer to apply a +/- 10 Vdc signal to the drive based on the desired output torque.

In a typical brushless dc servo system, three embedded loops with various compensation and filtering elements are present. The inner loop (the current loop) is controlled by the velocity loop, which in turn is controlled by the position loop. The current loop always resides in the drive, while the velocity and position loops reside in either the drive or controller. The current loop uses a motor current sensor to measure current in the motor windings, while the velocity loop uses a speed sensor (typically an encoder) to measure motor velocity, which also provides position information to close the position loop.

Motion controllers are microprocessor-based devices with complex algorithms that generate Pulse Width Modulated (PWM) waveforms. Power transistors within the servo drive transfer the current and voltage waveforms to energize the motor. The motion controller typically processes the feedback information from the various servo loops. Controllers use feedback information to commutate the motor to behave precisely as commanded by the microprocessor. In essence, the intelligence provided by the microprocessor acts as the controller, while the electronics associated with the power devices acts as the drive. Basically, a controller is the element that applies a specific command to a position, velocity, or current loop, while a drive provides the voltage and current to the motors as demanded by the controller.

The controller is typically a programmable device that stores and runs code provided by the programmer. Programming is developed in a variety of languages, such as BASIC, C+/C++, VB, and languages specified in IEC 61131-3 standards. Controllers have numerous safety elements to prevent overloads or stop motion in the event of component failures. Drives, on the other hand, tend to focus on receiving the input commands of the controller and switching the power transistors on and off. This creates the current and voltage required to meet the commanded torque and speed.

With advances in microprocessors and new switching devices, controllers and drives are becoming more and more intertwined – mostly in centralized systems where all electronics are co-located in a single control cabinet. In decentralized solutions, the motion controller resides in the cabinet while the drives are collocated near the motors and communicate with the centralized motion controller through a motion field bus.

Editor’s Note: This article was written by a team of motion and automation experts at Kollmorgen, including engineers, customer service and design experts.

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Two Kawasaki welding robots coordinate their motions using RealTime Robotics RapidPlan software. | Credit: RealTime Robotics

Realtime Robotics released its new RapidPlan software this week to help manufacturers design and deploy industrial automation faster and more efficiently.

RapidPlan helps automate the programming, deployment and control of industrial robots. The solution automatically calculates robot paths and avoids collisions during operations. RapidPlan is a unique solution for multi-robot workcells, where the work envelopes of the robots overlap and collisions are possible.

For industrial robots, complex workcells with intricate operations can take weeks to months to plan. Realtime Robotics is designed to abstract robot control regardless of the robot vendor and removes the need for brand-specific robot programming.

RapidPlan has a complete simulation environment that enables both offline programming of the robot as well as accelerating the robot deployment process. System integrators can effectively prepare all of the robot programming in simulation, even before the “metal” hits the production floor. The motions in simulation and as-built reality match, dramatically speeding up the design and deployment processes.

As robotic processes change over time or as requirements for optimization evolve, RapidPlan provides a programming environment that provide a highly-flexible solution. RapidPlan can use the information from PLCs (programmable logic controllers) or from dedicated 3D sensors to improve the planning and operations process.

“Optimizing the efficiency of your industrial and factory operations should not be held back by technical barriers,” added George Konidaris, co-founder and Chief Roboticist of Realtime Robotics. “We specifically designed RapidPlan to deliver an accurate simulation of robot task planning, making it easy to program models and use them directly on the factory floor, but did so in a way that streamlined the process and made the technology easy-to-use for all.”

Bin picking has traditionally been a challenging application for a multi-robot setup. Users don’t know the exact part location for picking, making it challenging to predict an accurate collision-free path for multiple robots that are completing tasks in the same area. With RapidPlan, robot space reservations are released in real time as soon as the robot moves to another location, dramatically improving cycle time or other parameters that users prioritize.

During the on-site physical validation stage, a manufacturer typically needs to have a highly-skilled team working after hours to manually run through every move combination, ensuring seamless operations on the live factory floor. Because RapidPlan inherently produces collision-free paths, it reduces the need to verify against potential collisions – resulting in significant time savings.

RapidPlan will alert the user of any potential collision beforehand, so steps can be taken to prevent it. If a cycle is interrupted for any reason, the user can easily and quickly return the robots to their home poses without needing to individually jog them home.

“The combination of Kawasaki’s quality robots, advanced programming platform and Realtime Robotics software is an industry game changer. Providing manufacturers from all industries with unprecedented flexibility, from automating programming of robotic motion and collision avoidance to the very design of the manufacturing floor. This is the future of automation, and the very best has yet to come,” added Kazuhiro Saito, President at Kawasaki Robotics.

Realtime Robotics RapidPlan software consists of two main components:

RapidPlan Create
With RapidPlan Create, users can easily create a digital twin workcell. Users import cell elements, such as CAD files or other components from a library, then click and point to create targets and goals. Realtime Robotics software automatically generates offline programs and interlock locations for industrial robots.

RapidPlan Control
RapidPlan Control makes collision-free operation a reality for industrial settings and factory floors. Customers can have confidence in robot motions and dynamic obstacle avoidance because of Realtime Robotics software. Motions remain collision-free, even after live floor changes. Automated fault recovery provides high flexibility and adaptability to robot cells.

The launch of RapidPlan marks a shift by Realtime Robotics towards software products, based on customer feedback, with the goal of making it even easier to integrate the company’s solutions into existing technology stacks. Realtime Robotics’ innovative RapidPlan software is compatible with engineering workstations, field laptops and industrial PCs, giving customers the option to utilize the software in their method of choice. RapidPlan’s modular flexibility empowers organizations to better scale their production lines across multiple factories, as their operations expand.

Realtime Robotics will also be on-site at Automate 2022 this week. Its executives will be giving presentations and its technology will be on display in demos at the Kawasaki Robotics Inc. booth (#2332) and the Mitsubishi Electric Automation booth (#1023).

Editors Note:

George Konidaris, co-founder and Chief Roboticist of Realtime Robotics was a guest on Episode 53 of the Robot Report Podcast.

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Celera Motion, a business unit of Novanta, expanded its direct drive motor platform, the Omni+ Series. The Omni+ Series is designed for optimal system integration, with a range of axial lengths and winding options. Known for exceling in motion smoothness and torque density, the pre-engineered frameless motor kit series has now been expanded to include a new size: the Omni+ 100 mm.

“The Omni+ Series delivers a ‘magic combination’ of motion smoothness and high torque density while offering an ideal form factor,” said Mike Mainvielle, VP product management & marketing of Celera Motion. “The motor kits are easy to integrate into a wide variety of applications, including surgical robots, satellite communications and collaborative robots. We’re very pleased to see so many companies embracing all that the Omni+ Series has to offer.”

The Omni+ Series include three motors. | Credit: Celera Motion

The OMNI+ Series motors come in three models designed to provide higher torque density and ultra-low cogging, resulting in smooth motion, lower power dissipation and decreased temperature rise. The technology provides high speeds and accelerations with superior mechanical stiffness, reducing settling times and increasing system performance and throughput.

Celera said the benefits of the Omni+ Series include:

• An innovative electromagnetic design that delivers elite torque density and a compact form factor
• A large ID-to-OD ratio for convenient routing of cables, optics and other system elements
• Size compatibility with common strain wave gears and a wide range of motor drives
• Minimal cogging for accurate and smooth motion
• Custom windings and form factors available to meet application requirements

The Omni+ Series fits into geared robotic joints, direct drive rotary stages or actuator applications for efficient utilization of space. Applications include:

• Surgical robotics
• Exoskeletons and wearables
• Satellite communications
• UAV gimbals
• Collaborative robots

Celera Motion introduced the Omni+ series in 2020. In addition to the Omni+ 100, Celera Motion offers the OMNI+ 60 mm and the OMNI+ 70 mm. The company said more sizes are planned.

In 2021, Novanta acquired acquiring Schneider Electric Motion USA for $115 million and ATI Industrial Automation for $172 million. After officially acquiring Schneider Electric Motion, Novanta renaming the company Novanta IMS.

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The driver is compatible across the entire line of UR robots, from 3 kg payload to 16 kg payload, and includes both the CB3 and the E-series. And supports key functionalities like:

• Pause at emergency stop and safeguard stop
• Resume after emergency and safeguard stops
• Automatic speed scaling to be within the safety settings
• Manual speed scaling from the teach pendant

The release is now available via rosdep binary for Galactic Geochelone and will also be available for Rolling Ridley and Humble Hawksbill.

You can read the installation instructions here and watch the ROS World 2021 presentation below. If you have feedback or comments about the new ROS 2 driver for UR’s cobots, send them to ROS@universal-robots.com

UR is the leading developer of cobot arms and owns roughly a 40% share of the entire market. FZI is a non-profit research institute for applied computer science in Karlsruhe, Germany established in 1985. PickNik Robotics is known for its motion-planning software called MoveIt, which is one of the more popular ROS-based motion planning platforms.

Teradyne acquired UR in 2015 for $285 million. Teradyne also owns AutoGuide Mobile Robots, Energid, Mobile Industrial Robots (MiR). The companies generated $80 million in Q1 2021 revenue.

As usual, UR led the way with record Q1 revenue of $85 million. That is up 30% when compared to revenue in Q1 2021. UR sales in the United States grew 55% in the quarter.

“We’re seeing broad-based growth from many different segments,” Greg Smith, president of Teradyne’s industrial automation group, told The Robot Report. “Customers have told us they’ve been facing labor shortages since the beginning of the pandemic. Now that they’ve realized those shortages aren’t going to get better, they’re investing in automation.”

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The OES FIGARO is a 1 to 4 axis motion controller available in a standard 19″ rack mountable unit. | Credit: OES

The OES FIGARO series is a NEW motion control system introduced to complement Optimal Engineering Systems’ growing line of single and multi-axis positioning stages. The FIGARO series is an easy-to-use, plug-and-play, cost effective solution motion controller.

The standard 1, 2, 3, and 4 axis FIGARO Motion Control Systems are available as compact, countertop enclosures or 19 inch rack mounts for Stepper Motors, DC Servo Motors with Quadrature Incremental Encoders, three-phase Brushless DC Servo Motors with Quadrature Incremental Encoders and Hall Effect Sensors, or Voice Coil motors with linear encoders.

Additionally, the FIGARO series can be configured with any combination of drivers for Steppers, DC Servos, and BLDC Motors.

An external host such as a PC, micro-controller or PLC sends commands to the Controller via a USB or RS-232 serial port, and the Controller processes and executes the commands. When commands are loaded into the controller’s memory, the controller is capable of running the commands without need of the host.

The FIGARO series works with host installed programs such as: C/C++, Python, Visual Basic, LabVIEWTM, and MATLABTM. Also, the System can be operated using an analog joystick or a trackball. Options include: HOME and LIMIT switches, TTL/CMOS Inputs and Outputs, Quadrature Encoder Feedback, and an Ethernet interface.

The FIGARO Motion Controllers can provide up to 7 Amps per phase current, and up to 256 micro-steps per step resolution, for stepping motors from NEMA 8 to 42; for DC Servos and BLDC motors up to 40 Amps per phase, and + 18 VDC to 80 VDC power supply voltage.

Easy to install and use these Motion Control Systems are totally integrated solutions featuring free software. The FIGARO Motion Control Systems operate on an input power of 115 or 230 VAC, 50-60 Hz, and can be ordered Plug-and-Play when ordering any one of the many single or multi-axis positioning stages that are available from OES.

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