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Why a soccer kick bends the ball path: SOLIDWORKS simulation

With SOLIDWORKS Flow Simulation, you can virtually test a ball's flight path and see the science behind its amazing trajectory. Visualize anything you want to test, including the physics that make a ball curve and dip, to optimize performance and reduce physical testing. See the SOLIDWORKS Flow Simulation study setup and learn about the Magnus effect where a spinning object moving through a fluid curves away from its straight path. [Credit: Screenshot courtesy of SOLIDWORKS]
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Lightning-fast in-line verification, high-performance barcode reading

The Omron VHV5 Barcode Reader now combines high-performance barcode reading and calibrated ISO verification in one device. Replacing offline sample checks, it delivers 100% inline verification at production speeds up to 1,200 parts per minute. With flexible lighting, the VHV5 easily inspects labels and Direct Part Marks, even on challenging curved or irregular surfaces.
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How to choose the right industrial Ethernet switch

Antaira Technologies breaks down 10 mission-critical capabilities separating industrial-grade switches from commercial compromises. Even if you aren't in IT engineering, you will find valuable networking knowledge in this guide to protect vital infrastructure.
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New CAM software cuts robotic machining deployment

At Automate (Booth #4476), RoboDK will showcase RoboDK CAM, which generates robotic machining programs directly from CAD files. Designed for easy deployment, it cuts setup time by up to 40%. Live demonstrations will show users how to create collision-free robot motion straight from CAD data, eliminating manual line-by-line coding.
Learn more about RoboDK CAM.

AI Tools You Can Use: What is OpenClaw? How do I get it and use it?

OpenClaw is trending big time right now, but what is it? The YouTubers over at Create a Pro Website run through the basics of what you need to know and how to implement it. Basically, OpenClaw is a next-gen 24/7 AI assistant that lives on your computer and can perform actions for you. You talk to it through a chat app. You can set it up to do real work such as alert you to important emails, answer emails for you, manage your calendar and travel, and so much more. There is a great intro video here and also a longer, very thorough step-by-step video to setting up OpenClaw.
View the OpenClaw intro video.
View the OpenClaw setup video.

New! 6-digit programmable display/controller

Bristol Instruments has released the OM 403UNI Series displays/ controllers, allowing users to monitor two or three simultaneous functions. Configured via OM Link software or front-panel buttons, they feature four- or six-digit displays with +/-0.05% of f.s. range accuracy. They function as numeric/bar-graph displays, controllers, data recorders, or accumulators. Additionally, they detect and alert users to error conditions like broken sensor wires.
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Mini edge AI systems for vision, generative AI

As enterprises transition from PoC to real-world edge AI deployment, Aetina has launched its Mini Series Edge AI systems. Powered by NVIDIA Jetson Orin Nano and NX modules, these compact, fanless systems deliver high-performance vision and generative AI inference. Engineered for demanding industrial environments, they offer flexible camera connectivity, space-saving designs, and long-term reliability to accelerate smart infrastructure.
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Thermal imaging on the quality control line

On a high-speed food and beverage line, what you can see is not always what is happening. Thermal imaging adds a different layer of control. Instead of relying on surface appearance, it measures heat distribution as seals are formed and products move through the line, providing continuous, 100% in-line inspection instead of just sampling.
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Built for the test bench, ready for the field

FUTEK's IDC150 Signal Conditioner packages high-performance signal conditioning in a rugged aluminum enclosure. Built for engineers needing accurate, synchronized data from strain gauge sensors, it fits prototyping and lab environments. The device connects seamlessly to existing setups and pairs with SENSIT software and Python APIs. It is ideal for compact, high-performance digital sensor evaluation.
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Automotive lighting systems simplified, optimized

The new MLX81119 from Melexis is an 18-channel LIN RGB LED controller with an integrated DC/DC converter, designed to simplify and optimize automotive lighting systems. By generating the LED supply voltage locally on chip, this unit significantly reduces power dissipation, external components, and space requirements in increasingly dense vehicle applications such as door panels, dashboards, and charge-port lighting.
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How healthy is your machine? Moisture-in-Oil Sensor

iST's Moisture-in-Oil Sensor is a compact, digital RH/T module that accurately and continuously monitors the water content in oils and fuels. This sensor does not simply measure the absolute water content -- it measures the relative saturation level in % RH or water activity aw in %. This means you get a direct picture of the current oil quality and can react in time. Applications include: marine engines and gearboxes, commercial and rail vehicles, wind turbines and generators, drilling and paper machines, and more. Eval kit available.
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World's first native color lidar sensors

Ouster Rev8 features the world's first patented native color lidar sensors. For the first time, a single lidar sensor can understand road signs, interpret brake lights, or simply capture the richness of planet Earth in survey-grade, colorized maps. Based on patented Ouster Silicon with embedded Fujifilm color science, the L4 chip boasts 42.9 GMACs of processing power, detection of up to 20 trillion photons per sec, and a 40-kHz measurement rate with picosecond timing precision. Sees up to 200 m.
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Real-world applications: 3D camera ensures precise aircraft cabin drilling

In modern aircraft production, precision is everything. In this application article, learn how an Ensenso 3D camera integrated into an automated process chain ensures accurate detection and alignment of drilling positions in aircraft cabin assembly using the CAD data of the aircraft frame.
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What are Onshape Custom Features?

Certified Onshape Professional Too Tall Toby explains how to supercharge your workflow using community-created tools. In this insightful tutorial, he dives into the world of FeatureScript -- the powerful coding language behind Onshape. Learn where to find new scripts and how to use them. Save time. Learn new skills, shortcuts, and maybe even better ways to do things. Incorporate Custom Features into your everyday work. Very useful.
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What can you do with touchless magnetic angle sensors?

Novotechnik has put together an informative video highlighting real-world applications for their RFC, RFE, and RSA Series touchless magnetic angle sensors. You may be surprised at the variety of off-highway, marine, material handling, and industrial uses. You'll learn how they work (using a Hall effect microprocessor to detect position) and their key advantages, including eliminated wear and tear on these non-mechanical components. We love when manufacturers provide such useful examples.
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Ultra-low power chips help make small robots more capable

An ultra-low power hybrid chip inspired by the brain could help give palm-sized robots the ability to collaborate and learn from their experiences. Combined with new generations of low-power motors and sensors, the new application-specific integrated circuit (ASIC) -- which operates on milliwatts of power -- could help intelligent swarm robots operate for hours instead of minutes.

To conserve power, the chips use a hybrid digital-analog time-domain processor in which the pulse-width of signals encodes information. The neural network IC accommodates both model-based programming and collaborative reinforcement learning, potentially providing the small robots larger capabilities for reconnaissance, search and rescue, and other missions.

Researchers from the Georgia Institute of Technology demonstrated robotic cars driven by the unique ASICs at the 2019 IEEE International Solid-State Circuits Conference (ISSCC). The research was sponsored by the Defense Advanced Research Projects Agency (DARPA) and the Semiconductor Research Corporation (SRC) through the Center for Brain-inspired Computing Enabling Autonomous Intelligence (CBRIC).

"We are trying to bring intelligence to these very small robots so they can learn about their environment and move around autonomously, without infrastructure," said Arijit Raychowdhury, associate professor in Georgia Tech's School of Electrical and Computer Engineering. "To accomplish that, we want to bring low-power circuit concepts to these very small devices so they can make decisions on their own. There is a huge demand for very small but capable robots that do not require infrastructure."

The cars demonstrated by Raychowdhury and graduate students Ningyuan Cao, Muya Chang, and Anupam Golder navigated through an arena floored by rubber pads and surrounded by cardboard block walls. As they searched for a target, the robots had to avoid traffic cones and each other, learning from the environment as they went and continuously communicating with each other.

The cars use inertial and ultrasound sensors to determine their location and detect objects around them. Information from the sensors goes to the hybrid ASIC, which serves as the "brain" of the vehicles. Instructions then go to a Raspberry Pi controller, which sends instructions to the electric motors.

VIDEO: Combined with new generations of low-power motors and sensors, the new application-specific integrated circuit (ASIC) could help intelligent swarm robots operate for hours instead of minutes.

In palm-sized robots, three major systems consume power: the motors and controllers used to drive and steer the wheels, the processor, and the sensing system. In the cars built by Raychowdhury's team, the low-power ASIC means that the motors consume the bulk of the power. "We have been able to push the compute power down to a level where the budget is dominated by the needs of the motors," he said.

The team is working with collaborators on motors that use micro-electromechanical (MEMS) technology able to operate with much less power than conventional motors.

"We would want to build a system in which sensing power, communications and computer power, and actuation are at about the same level, on the order of hundreds of milliwatts," said Raychowdhury, who is the ON Semiconductor Associate Professor in the School of Electrical and Computer Engineering. "If we can build these palm-sized robots with efficient motors and controllers, we should be able to provide runtimes of several hours on a couple of AA batteries. We now have a good idea what kind of computing platforms we need to deliver this, but we still need the other components to catch up."

In time domain computing, information is carried on two different voltages, encoded in the width of the pulses. That gives the circuits the energy-efficiency advantages of analog circuits with the robustness of digital devices.

"The size of the chip is reduced by half, and the power consumption is one-third what a traditional digital chip would need," said Raychowdhury. "We used several techniques in both logic and memory designs for reducing power consumption to the milliwatt range while meeting target performance."

With each pulse-width representing a different value, the system is slower than digital or analog devices, but Raychowdhury says the speed is sufficient for the small robots. (A milliwatt is a thousandth of a watt).

"For these control systems, we don't need circuits that operate at multiple gigahertz because the devices aren't moving that quickly," he said. "We are sacrificing a little performance to get extreme power efficiencies. Even if the compute operates at 10 or 100 megahertz, that will be enough for our target applications."

The 65-nanometer CMOS chips accommodate both kinds of learning appropriate for a robot. The system can be programmed to follow model-based algorithms, and it can learn from its environment using a reinforcement system that encourages better and better performance over time -- much like a child who learns to walk by bumping into things.

"You start the system out with a predetermined set of weights in the neural network so the robot can start from a good place and not crash immediately or give erroneous information," Raychowdhury said. "When you deploy it in a new location, the environment will have some structures that it will recognize and some that the system will have to learn. The system will then make decisions on its own, and it will gauge the effectiveness of each decision to optimize its motion."

Communication between the robots allows them to collaborate to seek a target.

"In a collaborative environment, the robot not only needs to understand what it is doing, but also what others in the same group are doing," he said. "They will be working to maximize the total reward of the group as opposed to the reward of the individual."

With their ISSCC demonstration providing a proof-of-concept, the team is continuing to optimize designs and is working on a system-on-chip to integrate the computation and control circuitry.

"We want to enable more and more functionality in these small robots," Raychowdhury added. "We have shown what is possible, and what we have done will now need to be augmented by other innovations."

This project was supported by the Semiconductor Research Corporation.

CITATION: Ningyuan Cao, Muya Chang, Arijit Raychowdhury, "A 65 nm 1.1-to-9.1 TOPS/W Hybrid-Digital-Mixed-Signal Computing Platform for Accelerating Model-Based and Model Free Swarm Robotics." (2019 IEEE International Solid-State Circuits Conference).

Source: Georgia Tech

Published March 2019

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