From Extremetech: The K5, built by the Californian company Knightscope, is billed rather euphemistically as an “autonomous data machine” that provides a “commanding but friendly physical presence.” Basically, it’s a security guard on wheels. Inside that rather large casing (it’s 5 foot tall!) there are four high-def cameras facing in each direction, another camera that can do car license plate recognition, four microphones, gentle alarms, blaring sirens, weather sensors, and WiFi connectivity so that each robot can contact HQ if there’s some kind of security breach/situation. For navigating the environment, there’s GPS and “laser scanning” (LIDAR I guess). And of course, at the heart of each K5 is a computer running artificial intelligence software that integrates all of that data and tries to make intelligent inferences... ( full article ) ( knightscope )
Mr. Jellen joins Adept after more than 10 years with Danaher Corporation, where he held successive roles of increasing responsibility, including vice president and general manager for various business units.
Richard Erb to Become Executive Director of RoboUniverse
The magazine has undergone a major content update and redesign
In the next decade, self-driving cars will revolutionize transportation worldwide.
Portwell's Intel Atom E3800 processor-based NANO-6060 helps power the students' unmanned surface vehicle (USV) to success
High-speed transfers reduce data bottlenecks and increase efficiency for high-end applications
Canadian robot makers accompany Yahoo!'s Marissa Mayer and Facebook's Mark Zuckerberg on 40 Under 40 list.
"Ecovacs Robotics is honored to receive the esteemed CES Innovation Award honoring outstanding design and engineering in consumer technology"
Du-Co Ceramics Integrates Robotics Into Ceramics Parts Manufacturing Process
"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"
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.
This solution is ideal for on-machine mounting and fast, precise format adjustment.
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 .
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Industrial Robotics - Featured Product
RTX64 turns the Microsoft 64-bit Windows operating system into a Real-time operating system (RTOS). RTX64 enhances Windows by providing hard real-time and control capabilities to a general purpose operating system that is familiar to both developers and end users. RTX64 consists of a separate real-time subsystem (RTSS) that schedules and controls all RTSS applications independently of Windows.RTX64 is a key component of the IntervalZero RTOS Platform that comprises x86 and x64 multicore multiprocessors, Windows, and real-time Ethernet (e.g. EtherCAT or PROFINET) to outperform real-time hardware such as DSPs and radically reduce the development costs for systems that require determinism or hard real-time.