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Choosing a stepper motor: PM or hybrid?

Lin Engineering stepper motors are widely used in various applications that require precise control of motion, such as in robotics, 3D printing, CNC machines, and medical equipment. There are two main types of stepper motors: permanent magnet (PM) and hybrid. Learn the differences, advantages, and when to use one type or the other.
Read this informative Lin Engineering article.

Top Product: Integrated servo system is 20% smaller than standalone unit

Applied Motion Products has introduced the MDX+ series, a family of low-voltage servo systems that integrate a servo drive, motor, and encoder into one package. This all-in-one drive unit is an ideal solution for manufacturers in logistics, AGV, medical, semiconductor, the solar industries, and many others.
Read the full article.

Overhung load adaptors provide load support and contamination protection

Overhung load adaptors (OHLA) provide both overhung radial and axial load support to protect electrified mobile equipment motors from heavy application loads, extending the lifetime of the motor and alleviating the cost of downtime both from maintenance costs and loss of production. They seal out dirt, grime, and other contaminants too. Zero-Max OHLAs are available in an extensive offering of standard models (including Extra-Duty options) for typical applications or customized designs.
Learn more.

Why choose electric for linear actuators?

Tolomatic has been delivering a new type of linear motion technology that is giving hydraulics a run for its money. Learn the benefits of electric linear motion systems, the iceberg principle showing total cost of ownership, critical parameters of sizing, and conversion tips.
Get this informative e-book. (No registration required)

New AC hypoid inverter-duty gearmotors

Bodine Electric Company introduces 12 new AC inverter-duty hypoid hollow shaft gearmotors. These type 42R-25H2 and 42R-30H3 drives combine an all-new AC inverter-duty, 230/460-VAC motor with two hypoid gearheads. When used with an AC inverter (VFD) control, these units deliver maintenance-free and reliable high-torque output. They are ideal for conveyors, gates, packaging, and other industrial automation equipment that demands both high torque and low power consumption from the driving gearmotor.
Learn more.

Next-gen warehouse automation: Siemens, Universal Robots, and Zivid partner up

Universal Robots, Siemens, and Zivid have created a new solution combining UR's cobot arms with Siemens' SIMATIC Robot Pick AI software and Zivid's 3D sensors to create a deep-learning picking solution for warehouse automation and intra-logistics fulfillment. It works regardless of object shape, size, opacity, or transparency and is a significant leap in solving the complex challenges faced by the logistics and e-commerce sectors.
Read the full article.

Innovative DuoDrive gear and motor unit is UL/CSA certified

The DuoDrive integrated gear unit and motor from NORD DRIVE-SYSTEMS is a compact, high-efficiency solution engineered for users in the fields of intralogistics, pharmaceutical, and the food and beverage industries. This drive combines a IE5+ synchronous motor and single-stage helical gear unit into one compact housing with a smooth, easy-to-clean surface. It has a system efficiency up to 92% and is available in two case sizes with a power range of 0.5 to 4.0 hp.
Learn more.

BLDC flat motor with high output torque and speed reduction

Portescap's 60ECF brushless DC slotted flat motor is the newest frame size to join its flat motor portfolio. This 60-mm BLDC motor features a 38.2-mm body length and an outer-rotor slotted configuration with an open-body design, allowing it to deliver improved heat management in a compact package. Combined with Portescap gearheads, it delivers extremely high output torque and speed reduction. Available in both sensored and sensorless options. A great choice for applications such as electric grippers and exoskeletons, eVTOLs, and surgical robots.
Learn more and view all the specs.

Application story: Complete gearbox and coupling assembly for actuator system

Learn how GAM engineers not only sized and selected the appropriate gear reducers and couplings required to drive two ball screws in unison using a single motor, but how they also designed the mounting adapters necessary to complete the system. One-stop shopping eliminated unnecessary components and resulted in a 15% reduction in system cost.
Read this informative GAM blog.

Next-gen motor for pump and fan applications

The next evolution of the award-winning Aircore EC motor from Infinitum is a high-efficiency system designed to power commercial and industrial applications such as HVAC fans, pumps, and data centers with less energy consumption, reduced emissions, and reduced waste. It features an integrated variable frequency drive and delivers upward of 93% system efficiency, as well as class-leading power and torque density in a low-footprint package that is 20% lighter than the previous version. Four sizes available.
Learn more.

Telescoping linear actuators for space-constrained applications

Rollon's new TLS telescoping linear actuators enable long stroke lengths with minimal closed lengths, which is especially good for applications with minimal vertical clearance. These actuators integrate seamlessly into multi-axis systems and are available in two- or three-stage versions. Equipped with a built-in automated lubrication system, the TLS Series features a synchronized drive system, requiring only a single motor to achieve motion. Four sizes (100, 230, 280, and 360) with up to 3,000-mm stroke length.
Learn more.

Competitively priced long-stroke parallel gripper

The DHPL from Festo is a new generation of pneumatic long-stroke grippers that offers a host of advantages for high-load and high-torque applications. It is interchangeable with competitive long-stroke grippers and provides the added benefits of lighter weight, higher precision, and no maintenance. It is ideal for gripping larger items, including stacking boxes, gripping shaped parts, and keeping bags open. It has high repetition accuracy due to three rugged guide rods and a rack-and-pinion design.
Learn more.

Extend your range of motion: Controllers for mini motors

FAULHABER has added another extremely compact Motion Controller without housing to its product range. The new MC3603 controller is ideal for integration in equipment manufacturing and medical tech applications. With 36 V and 3 A (peak current 9 A), it covers the power range up to 100 W and is suitable for DC motors with encoder, brushless drives, or linear motors.
Learn more.

When is a frameless brushless DC motor the right choice?

Frameless BLDC motors fit easily into small, compact machines that require high precision, high torque, and high efficiency, such as robotic applications where a mix of low weight and inertia is critical. Learn from the experts at SDP/SI how these motors can replace heavier, less efficient hydraulic components by decreasing operating and maintenance costs. These motors are also more environmentally friendly than others.
View the video.

Tiny and smart: Step motor with closed-loop control

Nanotec's new PD1-C step motor features an integrated controller and absolute encoder with closed-loop control. With a flange size of merely 28 mm (NEMA 11), this compact motor reaches a max holding torque of 18 Ncm and a peak current of 3 A. Three motor versions are available: IP20 protection, IP65 protection, and a motor with open housing that can be modified with custom connectors. Ideal for applications with space constraints, effectively reducing both wiring complexity and installation costs.
Learn more.

Amazon approved: Automated pick-and-place systems take a step forward with robo-picker that grasps, ‘feels,' and packs

This next-gen pick-and-place system consists of a standard industrial robotic arm that MIT researchers outfitted with a custom gripper and suction cup. They developed an "object-agnostic" grasping algorithm that enables the robot to assess a bin of random objects and determine the best way to grip or suction onto an item amid the clutter, without having to know anything about the object before picking it up. [Image: Melanie Gonick/MIT]

 

 

 

 

By Jennifer Chu, MIT

Unpacking groceries is a straightforward, albeit tedious, task: You reach into a bag, feel around for an item, and pull it out. A quick glance will tell you what the item is and where it should be stored.

Now engineers from MIT and Princeton University have developed a robotic system that may one day lend a hand with this household chore, as well as assist in other picking and sorting tasks, from organizing products in a warehouse to clearing debris from a disaster zone.

The team's "pick-and-place" system consists of a standard industrial robotic arm that the researchers outfitted with a custom gripper and suction cup. They developed an "object-agnostic" grasping algorithm that enables the robot to assess a bin of random objects and determine the best way to grip or suction onto an item amid the clutter, without having to know anything about the object before picking it up.

Once it has successfully grasped an item, the robot lifts it out from the bin. A set of cameras then takes images of the object from various angles, and with the help of a new image-matching algorithm the robot can compare the images of the picked object with a library of other images to find the closest match. In this way, the robot identifies the object, then stows it away in a separate bin.

In general, the robot follows a "grasp-first-then-recognize" workflow, which turns out to be an effective sequence compared to other pick-and-place technologies.

"This can be applied to warehouse sorting, but also may be used to pick things from your kitchen cabinet or clear debris after an accident. There are many situations where picking technologies could have an impact," says Alberto Rodriguez, the Walter Henry Gale Career Development Professor in Mechanical Engineering at MIT.

VIDEO: Robo-picker grasps and packs.

Rodriguez and his colleagues at MIT and Princeton will present a paper detailing their system at the IEEE International Conference on Robotics and Automation in May.

Building a library of successes and failures
While pick-and-place technologies may have many uses, existing systems are typically designed to function only in tightly controlled environments.

Today, most industrial picking robots are designed for one specific, repetitive task, such as gripping a car part off an assembly line, always in the same, carefully calibrated orientation. However, Rodriguez is working to design robots as more flexible, adaptable, and intelligent pickers for unstructured settings such as retail warehouses, where a picker may consistently encounter and have to sort hundreds, if not thousands of novel objects each day, often amid dense clutter.

The team's design is based on two general operations: picking (the act of successfully grasping an object) and perceiving (the ability to recognize and classify an object, once grasped).

The researchers trained the robotic arm to pick novel objects out from a cluttered bin, using any one of four main grasping behaviors: suctioning onto an object vertically; suctioning onto an object from the side; gripping the object vertically like the claw in an arcade game; or, for objects that lie flush against a wall, gripping vertically, then using a flexible spatula to slide between the object and the wall.

Rodriguez and his team showed the robot images of bins cluttered with objects, captured from the robot's vantage point. They then showed the robot which objects were graspable, with which of the four main grasping behaviors, and which were not, marking each example as a success or failure. They did this for hundreds of examples, and over time, the researchers built up a library of picking successes and failures. They then incorporated this library into a "deep neural network" -- a class of learning algorithms that enables the robot to match the current problem it faces with a successful outcome from the past, based on its library of successes and failures.

"We developed a system where, just by looking at a tote filled with objects, the robot knew how to predict which ones were graspable or suctionable, and which configuration of these picking behaviors was likely to be successful," Rodriguez says. "Once it was in the gripper, the object was much easier to recognize, without all the clutter."

From pixels to labels
The researchers developed a perception system in a similar manner, enabling the robot to recognize and classify an object once it's been successfully grasped.

To do so, they first assembled a library of product images taken from online sources such as retailer websites. They labeled each image with the correct identification -- for instance, duct tape versus masking tape -- and then developed another learning algorithm to relate the pixels in a given image to the correct label for a given object.

"We're comparing things that, for humans, may be very easy to identify as the same, but in reality, as pixels, they could look significantly different," Rodriguez says. "We make sure that this algorithm gets it right for these training examples. Then the hope is that we've given it enough training examples that, when we give it a new object, it will also predict the correct label."

Last July, the team packed up the 2-ton robot and shipped it to Japan, where, a month later, they reassembled it to participate in the Amazon Robotics Challenge, a yearly competition sponsored by the online megaretailer to encourage innovations in warehouse technology. Rodriguez's team was one of 16 taking part in a competition to pick and stow objects from a cluttered bin.

In the end, the team's robot had a 54 percent success rate in picking objects up using suction and a 75 percent success rate using grasping, and was able to recognize novel objects with 100 percent accuracy. The robot also stowed all 20 objects within the allotted time.

For his work, Rodriguez was recently granted an Amazon Research Award and will be working with the company to further improve pick-and-place technology -- foremost, its speed and reactivity.

"Picking in unstructured environments is not reliable unless you add some level of reactiveness," Rodriguez says. "When humans pick, we sort of do small adjustments as we are picking. Figuring out how to do this more responsive picking, I think, is one of the key technologies we're interested in."

The team has already taken some steps toward this goal by adding tactile sensors to the robot's gripper and running the system through a new training regime.

"The gripper now has tactile sensors, and we've enabled a system where the robot spends all day continuously picking things from one place to another. It's capturing information about when it succeeds and fails, and how it feels to pick up, or fails to pick up, objects," Rodriguez says. "Hopefully, it will use that information to start bringing that reactiveness to grasping."

This research was sponsored in part by ABB Inc., Mathworks, and Amazon.

Published February 2018

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