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Universal Robots Offers Rapid Response Delivery, Enabling Manufacturers to Meet Tax Deduction Deadline

With an industry leading manufacturing process, Universal Robots can meet delivery deadlines for the Section 179 tax deduction incentive that can dramatically reduce the cost of collaborative robots to address repetitive and difficult-to-fill manufacturing jobs

How to dance to a synthetic band

Music plays an important role in most people's lives regardless of the genre and in a wide variety of contexts from celebrations and parties to simply providing background while a task is being performed. Until very recently, music was only heard when musicians played it live, the ability to record music displaced that live performance to some degree, and then the invention of electronic musical instruments and digitisation changed our appreciation of music yet again.

HALCON 18.11 – MVTec’s powerful machine vision software with a huge range of deep learning functions – Free trial!

The newest version of MVTec HALCON is here to solve all of your machine vision tasks at utmost speed and robustness! Deep learning functions, like pixel-precise semantic segmentation or object detection, help you to identify and classify objects and flaws more flexibly and easier than ever before – HALCON extracts relevant image information automatically. Try it for free here!

AdaSearch: A successive elimination approach to adaptive search

By Esther Rolf∗, David Fridovich-Keil∗, and Max Simchowitz

In many tasks in machine learning, it is common to want to answer questions given fixed, pre-collected datasets. In some applications, however, we are not given data a priori; instead, we must collect the data we require to answer the questions of interest.

This situation arises, for example, in environmental contaminant monitoring and census-style surveys. Collecting the data ourselves allows us to focus our attention on just the most relevant sources of information. However, determining which of these sources of information will yield useful measurements can be difficult. Furthermore, when data is collected by a physical agent (e.g. robot, satellite, human, etc.) we must plan our measurements so as to reduce costs associated with the motion of the agent over time. We call this abstract problem embodied adaptive sensing.

We introduce a new approach to the embodied adaptive sensing problem, in which a robot must traverse its environment to identify locations or items of interest. Adaptive sensing encompasses many well-studied problems in robotics, including the rapid identification of accidental contamination leaks and radioactive sources, and finding individuals in search and rescue missions. In such settings, it is often critical to devise a sensing trajectory that returns a correct solution as quickly as possible.

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Robotically fabricated concrete façade mullions installed in DFAB House

Credit:

To celebrate the installation of the concrete façade mullions digitally fabricated using Smart Dynamic Casting in the DFAB House, we have released a new extended video showing the entire process from start to finish.

Smart Dynamic Casting (SDC) is a continuous robotic slip-forming process that enables the prefabrication of material-optimised load-bearing concrete structures using a formwork significantly smaller than the structure produced. Read more about the project on the DFAB House website.

Smart Dynamic Casting is a collaborative research project of Gramazio Kohler Research, ETH Zurich, the Institute for Building Materials, ETH Zurich and the Institute of Structural Engineering, ETH Zurich. As part of the DFAB HOUSE project at the Empa and Eawag NEST research and innovation construction site in Dübendorf Smart Dynamic Casting is used for the automated prefabrication of material-optimised load-bearing concrete mullions.

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