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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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Closed loop steppers drive new motion control applications

According to the motion experts at Performance Motion Devices, when it comes to step motors, the drive technique called closed loop stepper is making everything old new again and driving a burst of interest in the use of two-phase step motors. It's "winning back machine designers who may have relegated step motors to the category of low cost but low performance."
Read this informative Performance Motion Devices article.

Intelligent compact drives with extended fieldbus options

The intelligent PD6 compact drives from Nanotec are now available with Profinet and EtherNet/IP. They combine motor, controller, and encoder in a space-saving package. With its 80-mm flange and a rated power of 942 W, the PD6-EB is the most powerful brushless DC motor of this product family. The stepper motor version has an 86-mm flange (NEMA 34) and a holding torque up to 10 Nm. Features include acceleration feed forward and jerk-limited ramps. Reduced installation time and wiring make the PD6 series a highly profitable choice for machine tools, packaging machines, or conveyor belts.
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Army research enables robots to learn new concepts and ask clarifying questions

Army researchers have developed a novel computational model that allows robots to ask clarifying questions to Soldiers. [Credit: 1st Lt. Angelo Mejia, U.S. Army]

 

 

 

 

U.S. Army researchers have developed a novel computational model that allows robots to ask clarifying questions to Soldiers, enabling them to be more effective teammates in tactical environments.

Future Army missions will have autonomous agents, such as robots, embedded in human teams making decisions in the physical world.

One major challenge toward this goal is maintaining performance when a robot encounters something it has not previously seen -- for example, a new object or location.

Robots will need to be able to learn these novel concepts on the fly in order to support the team and the mission.

"Our research explores a novel method for this kind of robot learning through interactive dialogue with human teammates," said Dr. Felix Gervits, researcher at the U.S. Army Combat Capabilities Development Command, known as DEVCOM, Army Research Laboratory (ARL). "We created a computational model for automated question generation and learning. The model enables a robot to ask effective clarification questions based on its knowledge of the environment and to learn from the responses. This process of learning through dialogue works for learning new words, concepts, and even actions."

Researchers integrated this model into a cognitive robotic architecture and demonstrated that this approach to learning through dialogue is promising for Army applications.

This research represents the culmination of a multi-year DEVCOM ARL project funded under the Office of the Secretary of Defense Laboratory University Collaboration Initiative, or LUCI, program for joint work with Tufts University and the Naval Research Laboratory.

In previous research, Gervits and team conducted an empirical study to explore and model how humans ask questions when controlling a robot. This led to the creation of the Human-Robot Dialogue Learning (HuRDL) corpus, which contains labeled dialogue data that categorizes the form of questions that study participants asked.

The HuRDL corpus serves as the empirical basis for the computational model for automated question generation, Gervits said.

Army researchers present an expanded dialogue example using the computational model for question generation in which a robot is verbally instructed to perform a task in an unexplored environment. The robot is able to learn the names of objects and locations as well as goals by asking clarifying questions. [Credit: U.S. Army Graphic]

 

 

 

 

The model uses a decision network, which is a probabilistic graphical model that enables a robot to represent world knowledge from its various sensory modalities, including vision and speech. It reasons over these representations to ask the best questions to maximize its knowledge about unknown concepts.

For example, he said, if a robot is asked to pick up some object that it has never seen before, it might try to identify the object by asking a question such as "What color is it?" or another question from the HuRDL corpus.

The question generation model was integrated into the Distributed Integrated Affect Reflection Cognition, or DIARC, robot architecture originating from collaborators at Tufts University.

In a proof-of-concept demonstration in a virtual Unity 3D environment, the researchers showed a robot learning through dialogue to perform a collaborative tool organization task.

Gervits said while prior ARL research on Soldier-robot dialogue enabled robots to interpret Soldier intent and carry out commands, there are additional challenges when operating in tactical environments.

For example, a command may be misunderstood due to loud background noise, or a Soldier can refer to a concept to which a robot is unfamiliar. As a result, Gervits said, robots need to learn and adapt on the fly if they are to keep up with Soldiers in these environments.

"With this research, we hope to improve the ability of robots to serve as partners in tactical teams with Soldiers through real-time generation of questions for dialogue-based learning," Gervits said. "The ability to learn through dialogue is beneficial to many types of language-enabled agents, such as robots, sensors, etc., which can use this technology to better adapt to novel environments."

Such technology can be employed on robots in remote collaborative interaction tasks such as reconnaissance and search-and-rescue, or in co-located human-agent teams performing tasks such as transport and maintenance.

This research is different from existing approaches to robot learning in that the focus is on interactive human-like dialogue as a means to learn. This kind of interaction is intuitive for humans and prevents the need to develop complex interfaces to teach the robot, Gervits said.

Another innovation of the approach is that it does not rely on extensive training data like so many deep learning approaches.

Deep learning requires significantly more data to train a system, and such data is often difficult and expensive to collect, especially in Army task domains, Gervits said. Moreover, there will always be edge cases that the system hasn't seen, and so a more general approach to learning is needed.

Finally, this research addresses the issue of explainability.

"This is a challenge for many commercial AI systems in that they cannot explain why they made a decision," Gervits said. "On the other hand, our approach is inherently explainable in that questions are generated based on a robot's representation of its own knowledge and lack of knowledge. The DIARC architecture supports this kind of introspection and can even generate explanations about its decision-making. Such explainability is critical for tactical environments, which are fraught with potential ethical concerns."

When combined with other related research at ARL such as the statistical language classifier and the Joint Understanding and Dialogue Interface, or JUDI, this research supports the broad goal of developing an advanced speech interface that can be utilized in various kinds of language-enabled autonomous systems for more effective Soldier-machine interaction.

"I am optimistic that this research will lead to a technology that will be used in a variety of Army applications," Gervits said. "It has the potential to enhance robot learning in all kinds of environments and can be used to improve adaptation and coordination in Soldier-robot teams."

The next step is to improve the model by expanding the kinds of questions it can ask.

This is not trivial, Gervits said, because some questions are so open-ended that they present a challenge to interpret the response.

For example, a question from the robot such as, "What does the object look like?" can elicit a variety of responses from a Soldier that are challenging for the robot to interpret.

A workaround is to develop dialogue strategies that robots can use that prioritize automated questions that can be easily interpreted, for example, "What shape is it?"

These are not always good questions, Gervits said, so a balance needs to be struck.

While the researchers' proof-of-concept demonstration shows this technology operating as part of a robot architecture in a virtual environment, they hope to validate it in physical environments in the near future as part of the AI for Maneuver and Mobility Essential Research Program.

"The physical world has additional challenges that robots need to overcome, including noisy sensor readings and potential for mechanical failure, and so such environments will serve as a stronger benchmark of performance," Gervits said.

Researchers will present their findings at the 23rd ACM International Conference on Multimodal Interaction in October 2021 and publish a paper in the conference proceedings.

Source: U.S. Army DEVCOM Army Research Laboratory

Published September 2021

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