CLEARPATH CO-FOUNDERS ARE 40 UNDER 40: PEOPLE TO WATCH IN 2015

Canadian robot makers accompany Yahoo!'s Marissa Mayer and Facebook's Mark Zuckerberg on 40 Under 40 list.

ECOVACS ROBOTICS NAMED AS 2015 CES INNOVATION AWARDS HONOREE

"Ecovacs Robotics is honored to receive the esteemed CES Innovation Award honoring outstanding design and engineering in consumer technology"

Ceramics Manufacturer 'Fires Up' its Production Line with Rethink Robotics' Baxter

Du-Co Ceramics Integrates Robotics Into Ceramics Parts Manufacturing Process

Unmanned Team Of K-MAX Helicopter And Indago Quad Rotor Demonstrate Firefighting Capability

"The unmanned K-MAX and Indago aircraft can work to fight fires day and night, in all weather, reaching dangerous areas without risking a life"

Kairos Autonomi Honored with Robotic Business Review Game Changer Award

Award honors robotic industry's remarkable technical accomplishments and their makers.

3D Robotics Launches X8+ Ready-to-Fly Personal Drone with Expandable Payload Capacity, Introduces FPV Kit

The ruggedized X8+ not only has the power to carry professional mirrorless system cameras, but also provides the lifting capacity to do delivery and real work, making it much more than a flying camera.

Festo Introduces Its All-in-One DC Servo Motor/Drive Unit - The MTR-ECI

This solution is ideal for on-machine mounting and fast, precise format adjustment.

Deep Visual-Semantic Alignments for Generating Image Descriptions

Because of the Nov. 14th submission  deadline for this years IEEE Conference on Computer Vision and Pattern Recognition (CVPR) several big image-recognition papers are coming out this week: From Andrej Karpathy and Li Fei-Fei of Stanford: We present a model that generates free-form natural language descriptions of image regions. Our model leverages datasets of images and their sentence descriptions to learn about the inter-modal correspondences between text and visual data. Our approach is based on a novel combination of Convolutional Neural Networks over image regions, bidirectional Recurrent Neural Networks over sentences, and a structured objective that aligns the two modalities through a multimodal embedding. We then describe a Recurrent Neural Network architecture that uses the inferred alignments to learn to generate novel descriptions of image regions. We demonstrate the effectiveness of our alignment model with ranking experiments on Flickr8K, Flickr30K and COCO datasets, where we substantially improve on the state of the art. We then show that the sentences created by our generative model outperform retrieval baselines on the three aforementioned datasets and a new dataset of region-level annotations... ( website with examples ) ( full paper ) From Oriol Vinyals, Alexander Toshev, Samy Bengio, and Dumitru Erhan at Google: Show and Tell: A Neural Image Caption Generator  ( announcement post ) ( full paper ) From Ryan Kiros, Ruslan Salakhutdinov, Richard S. Zemel at University of Toronto: Unifying Visual-Semantic Embeddings with Multimodal Neural Language Models  ( full paper ) From Junhua Mao, Wei Xu, Yi Yang, Jiang Wang and Alan L. Yuille at Baidu Research/UCLA: Explain Images with Multimodal Recurrent Neural Networks  ( full paper ) From Jeff Donahue, Lisa Anne Hendricks, Sergio Guadarrama, Marcus Rohrbach, Subhashini Venugopalan, Kate Saenko, and Trevor Darrell at UT Austin, UMass Lowell and UC Berkeley: Long-term Recurrent Convolutional Networks for Visual Recognition and Description ( full paper ) All these came from this Hacker News discussion .

DARPA-Funded Inflatable Robotics Helps Spark Idea for Silver Screen Star

Make-believe soft robot in Disney's newest movie has roots in real-world robotics research

Researchers Make Self-Learning Robots using 3D Printers

On the third floor of the Department of Informatics there is a robotics laboratory which looks like a playroom This is where researchers are testing how their robots can figure out how to move past barriers and other obstacles.

Opto Diode's New Quadrant Photodiode 5 mm² - SXUVPS4

The SXUVPS4 photodiodes are ideal for laser alignment applications

Gearing Up for A Smarter Future: SVForum presents "iHuman: The Future of Minds and Machines"

"iHuman: The Future of Minds and Machines," to be held on December 4th, 2014, in Silicon Valley, California

PINC Air Elevates Supply Chain Execution to New Heights

PINC Solutions announces an innovative aerial robotic RTLS product.

Kickstarter - UberBlox modular metal construction set to launch via Kickstarter

A new metal construction and prototyping set with a unique single-connector mechanism allows makers to create sophisticated structures and automated machines quickly and accurately. (see pre-launch video at uberblox.com)

Schunk - Cleanroom Gripper for Small to Medium Part Handling

The EGS from SCHUNK is perfect for the gripping of small to medium sized workpieces, with flexible force and high speed in clean environments, such as assembly, testing, laboratory, and the pharmaceutical industry.

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Industrial Robotics - Featured Product

Universal Robots - Collaborative Robot Solutions

Universal Robots - Collaborative Robot Solutions

Universal Robots is a result of many years of intensive research in robotics. The product portfolio includes the UR5 and UR10 models that handle payloads of up to 11.3 lbs. and 22.6 lbs. respectively. The six-axis robot arms weigh as little as 40 lbs. with reach capabilities of up to 51 inches. Repeatability of +/- .004" allows quick precision handling of even microscopically small parts. After initial risk assessment, the collaborative Universal Robots can operate alongside human operators without cumbersome and expensive safety guarding. This makes it simple and easy to move the light-weight robot around the production, addressing the needs of agile manufacturing even within small- and medium sized companies regarding automation as costly and complex. If the robots come into contact with an employee, the built-in force control limits the forces at contact, adhering to the current safety requirements on force and torque limitations. Intuitively programmed by non-technical users, the robot arms go from box to operation in less than an hour, and typically pay for themselves within 195 days. Since the first UR robot entered the market in 2009, the company has seen substantial growth with the robotic arms now being sold in more than 50 countries worldwide.