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 Disneys 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.
DJI Inspire 1
DJI's new Inspire 1 with 4K camera( $2899 USD from DJI ):
Aircraft specs:
Hovering Accuracy (GPS Mode)
Vertical: 1.6' / 0.5 m
Horizontal: 8.2' / 2.5 m
Maximum Angular Velocity
Pitch: 300°/s
Yaw: 150°/s
Maximum Tilt Angle
35°/s
Maximum Ascent/Descent Speed
Ascent: 16.4 fps / 5 m/s
Descent: 13.1 fps / 4 m/s
Maximum Speed
72.2 fps / 22 m/s (Attitude mode; no wind)
Maximum Flight Altitude
14,764' / 4,500 m
Maximum Wind Speed Resistance
32.8 fps / 10 m/s
Maximum Flight Time
Up to 18 minutes
Camera:
Model
Name: X3
Designation: FC350
Sensor
Sony EXMOR 1/2.3" CMOS
Resolution
12.0 MP
Lens
Field of View: 94°
Focal Length (35 mm Equivalent): 20 mm
Aperture: f/2.8
Design: 9 elements in 9 groups; aspherical lens element
Filters: Anti-distortion filter; UV filter
Video Recording
UHD (4K):
4096 x 2160: 24p, 25p
3840 x 2160: 24p, 25p, 30p
FHD (1080p):
1920 x 1080: 24p, 25p, 30p, 48p, 50p, 60p
HD (720p):
1280 x 720: 24p, 25p, 30p, 48p, 50p, 60p
Maximum Biterate: 60 Mbp/s
File Format
Photo: JPEG, DNG
Video: MP4 in a .MOV wrapper （MPEG-4 AVC/H.264）
Recording Media
Type: microSD/SDHC/SDXC up to 64 GB
Speed: Class 10 or faster
Format: FAT32/exFAT
Photography Modes
Single shot
Burst: 3, 5, 7 frames per second (AEB: 3/5 frames per second; 0.7 EV bias)
Time-lapse
Operating Temperature
32 to 104°F / 0 to 40°C
Gimbal:
Model
Zenmuse X3
Number of Axes
3-axis
Control Accuracy
±0.03°
Maximum Controlled Rotation Speed
Pitch: 120°/s
Pan: 180°/s
Controlled Rotation Range
Pitch: -90° to +30°
Pan: ±330°
Angular Vibration Range
±0.03°
Output Power
Static: 9 W
In Motion: 11 W
Operational Current
Static: 750 mA
In Motion: 900 mA
Mounting
Detachable
Video with required "Johnny Ives-alike" introductory speech:
Project Beyond: 360° 3D Camera
From Project Beyond/Samsung:
Today we offer a sneak preview of Project Beyond,the world’s first true 3D 360˚ omniview camera. Beyond captures and streams immersive videos in stunning high-resolution 3D, and allows every user to enjoy their viewing experience in the way they see fit. It offers full 3D reconstruction in all directions, using stereo camera pairs combined with a top-view camera to capture independent left and right eye stereo pairs.
Project Beyond uses patent-pending stereoscopic interleaved capture and 3D-aware stitching technology to capture the scene just like the human eye, but in a form factor that is extremely compact. The innovative reconstruction system recreates the view geometry in the same way that the human eyes see, producing unparalleled 3D perception.
Project Beyond is not a product, but one of the many exciting projects currently being developed by the Think Tank Team, an advanced research team within Samsung Research America. This is the first operational version of the device, and just a taste of what the final system we are working on will be capable of. Once complete, we hope to deploy Project Beyond around the world to beautiful and noteworthy locations and events, and allow users to experience those locations as if they were really there. The camera system can stream real time events, as well as store the data for future viewing... ( website )
Are Ag Robots Ready? 27 Companies Profiled
This article profiles 27 of the many companies (from conglomerates to start-ups) attempting to provide robotic solutions for farming problems and explores what they are doing, when their products will be available, and at what cost.
TUSExpo announces first speakers
TUSExpo has announced its first speakers scheduled to present during the first European Unmanned Systems trade show and conference, taking place 4-6 February 2015 in the World Forum, The Hague.
NEW CEO AT KUKA ROBOTICS CORPORATION US
Mr. Gemma brings over 29 years of relevant industry experience to his new role at KUKA Robotics Corporation.
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Industrial Robotics - Featured Product
Schmalz Technology Development - Vacuum Generation without Compressed Air - Flexible and Intelligent
• Vacuum generation that's 100% electrical;
• Integrated intelligence for energy and process control;
• Extensive communication options through IO-Link interface;
Schmalz already offers a large range of solutions that can optimize handling process from single components such as vacuum generators to complete gripping systems. Particularly when used in autonomous warehouse, conventional vacuum generation with compressed air reaches its limits. Compressed air often is unavailable in warehouses. Schmalz therefore is introducing a new technology development: a gripper with vacuum generation that does not use compressed air. The vacuum is generated 100% electrically. This makes the gripper both energy efficient and mobile. At the same time, warehouses need systems with integrated intelligence to deliver information and learn. This enables the use of mobile and self-sufficient robots, which pick production order at various locations in the warehouse. Furthermore, Schmalz provides various modular connection options from its wide range of end effectors in order to handle different products reliably and safely.
