From Leah Burrows and Harvard: A team of Harvard University researchers with expertise in 3-D printing, mechanical engineering, and microfluidics has demonstrated the first autonomous, untethered, entirely soft robot. This small, 3-D-printed robot — nicknamed the “octobot” — could pave the way for a new generation of such machines... ...Through our hybrid assembly approach, we were able to 3-D print each of the functional components required within the soft robot body, including the fuel storage, power, and actuation, in a rapid manner,” said Lewis. “The octobot is a simple embodiment designed to demonstrate our integrated design and additive fabrication strategy for embedding autonomous functionality.”... (full article)
The devices and technology enhance the capabilities of a human surgeon allowing them to perform better than they can "free hand," and potentially allow them to remain active for many more years than has been typical in the past.
Under the automation and robotics cluster, the BOI (Thailand Board of Investment) promotes projects investing in automation machinery and/or automation equipment with engineering design and assembling of robots or automation equipment and/or parts.
The latest revolutionary robot isn’t the metallic, costly machine you’d expect: It’s squishy like Silly Putty, wireless, battery-less and made for pennies by a 3D printer. Meet Octobot. It looks like a tiny octopus and is designed to mimic that slithery creature to get through cracks and tight places, making it ideal as a rescue robot. A team at Harvard University has created a robot - actually about 300 of them, since they are so cheap to make - that is opposite of the common view of a robot. Soft, not hard. Flexibl,e not rigid. It’s not mechanical, nor electrical. It’s powered by fluids. The discovery is described, photographed and shown on video in the scientific journal Nature. Cont'd...
If a robot gets a company's product out the door one or two days sooner, that equates to revenue, and thus cash, in the door one or two days sooner.
Kelsey D. Atherton for Popular Science: Flying machines are hard secrets to keep. By their very nature, they soar into the heavens, above the heads of those below. America's military tends to keep its secret planes secret by only flying them in vast swathes of empty desert, until they’re ready for public debut. But that’s not really an option for Amazon, which is testing delivery drones in the United Kingdom (while it attempts to weave its way through U.S. regulations). So where, exactly, are Amazon drones flying? A field eight miles south of Cambridge named “Worsted Lodge.” No, really. In a thorough photo-essay at Business Insider, reporter Sam Shead pinpoints and explores the site and the field, until turned away by a security guard. Cont'd...
The electroadhesive clutch is a general-purpose clutch for exoskeletons, offering increased functionality while being lightweight and consuming very little energy.
The surgical robot device market was estimated to be $3.2 billion in 2014 and forecast to reach $20 billion by 2021 as next generation devices, systems and instruments are introduced to manage surgery through small ports in the body instead of large open wounds.
Humans will always be required within an operation because they will need to process the one-off transactions that the robot has not been equipped to handle, and the robot will need to be programmed for any process changes.
Lauren Goode for The Verge: Pepper, the humanoid robot created by Aldebaran Robotics and SoftBank Mobile, is slowly making its way to the US — and it’s starting in Silicon Valley. The robot was seen in action this week at the b8ta store in Palo Alto, California, a gadget shop launched by former Nest employees. Pepper was on a demo loop at the store, so we weren’t able to fully interact with it. But the idea behind Pepper is that it’s supposed to interpret and respond to a variety of customer needs. Using a combination of 2D and 3D cameras in its eyes and mouth, plus four multi-directional microphones, Pepper is able to "read" four human emotions — happiness, joy, sadness, and anger — and respond accordingly. It rolls up to you, raises its hands in greeting when you introduce yourself, and turns its head toward you when you move or talk. It is toylike and adorable. Cont'd...
Source - Sky News: An insect-sized spy drone with four flapping wings and four legs is set to become Britain's latest weapon in the war on terror. The Dragonfly drone fits in the palm of a hand and has four flapping wings and four legs. It can fly through the air with great agility, allowing it to penetrate buildings through open windows, and perch on surfaces to eavesdrop. It can detect incoming objects and buildings, meaning it can avoid obstacles at high speeds. It is one of a number of pieces of kit being developed by the Ministry of Defence as part of an innovation drive. Cont'd...
Many police departments have purchased or plan to buy drones for search-and-rescue, arson, disaster relief, and accident investigations. Police officials say the devices can keep officers out of dangerous situations and cover more ground quickly, especially in the case of a missing child or an armed suspect on the run, especially in rural areas.
Our programs are all-inclusive. We provide the robots, and a login to a learning portal with all the lessons, exercises, and the programming interface.
A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimation
From Computer Vision Freiburg: Recent work has shown that optical flow estimation can be formulated as a supervised learning task and can be successfully solved with convolutional networks. Training of the so-called FlowNet was enabled by a large synthetically generated dataset. The present paper extends the concept of optical flow estimation via convolutional networks to disparity and scene flow estimation. To this end, we propose three synthetic stereo video datasets with sufficient realism, variation, and size to successfully train large networks. Our datasets are the first large-scale datasets to enable training and evaluating scene flow methods. Besides the datasets, we present a convolutional network for real-time disparity estimation that provides state-of-the-art results. By combining a flow and disparity estimation network and training it jointly, we demonstrate the first scene flow estimation with a convolutional network. his video shows impressions from various parts of our dataset, as well as state-of-the-art realtime disparity estimation results produced by one of our new CNNs... (full paper)
In the long term, job roles will shift away from their traditional remits and evolve to meet the needs of the modern, automated workplace.
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