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by   -   September 18, 2018

The multi-joint soft exosuit consists of textile apparel components worn at the waist, thighs and calves that guide mechanical forces from an optimized mobile actuation system attached to a rucksack via cables to the ankle and hip joints. In addition, a new tuning method helps personalize the exosuit’s effects to wearers’ specific gaits. Credit: Harvard Biodesign Lab

By Benjamin Boettner

In the future, smart textile-based soft robotic exosuits could be worn by soldiers, fire fighters and rescue workers to help them traverse difficult terrain and arrive fresh at their destinations so that they can perform their respective tasks more effectively. They could also become a powerful means to enhance mobility and quality of living for people suffering from neurodegenerative disorders and for the elderly.

by   -   September 18, 2018

MIT computer scientists have developed a system that learns to identify objects within an image, based on a spoken description of the image.
Image: Christine Daniloff

By Rob Matheson

MIT computer scientists have developed a system that learns to identify objects within an image, based on a spoken description of the image. Given an image and an audio caption, the model will highlight in real-time the relevant regions of the image being described.

by   -   September 18, 2018

Open-Source Software for robots is a de-facto standard in academia, and its advantages can benefit industrial applications as well. The worldwide ROS-Industrial initiative has been using ROS, the Robot Operating System, to this end.

by   -   September 10, 2018

Credit: Wyss Institute Harvard

By Benjamin Boettner

Manipulating delicate tissues such as blood vessels during difficult surgeries, or gripping fragile organisms in the deep sea presents a challenge to surgeons and researchers alike. Roboticists have made inroads into this problem by developing soft actuators on the microscale that are made of elastic materials and, through the expansion or contraction of embedded active components, can change their shapes to gently handle objects without damaging them. However, the specific designs and materials used for their fabrication so far still limit their range of motion and the strength they can exert at scales on which surgeons and researchers would like to use them.

by   -   September 10, 2018
With the DON system, a robot can do novel tasks like look at a shoe it has never seen before and successfully grab it by its tongue.
Photo: Tom Buehler/CSAIL

Humans have long been masters of dexterity, a skill that can largely be credited to the help of our eyes. Robots, meanwhile, are still catching up.

by   -   September 10, 2018

Applications from 166 companies spread across 12 European countries and myriads of exiting robotics ideas was the beginning of the EU-funded initiative ROBOTT-NET in 2016.

by   -   September 10, 2018

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In this post, we demonstrate how deep reinforcement learning (deep RL) can be used to learn how to control dexterous hands for a variety of manipulation tasks. We discuss how such methods can learn to make use of low-cost hardware, can be implemented efficiently, and how they can be complemented with techniques such as demonstrations and simulation to accelerate learning.

by   -   August 29, 2018

If you follow the robotics community on the twittersphere, you’ll have noticed that Rodney Brooks is publishing a series of essays on the future of robotics and AI which has been gathering wide attention.

by   -   August 23, 2018

In this episode of Robots in Depth, Per Sjöborg speaks with Søren Peter Johansen from DTI about implementing robotic solutions.

by   -   August 23, 2018

We are excited to announce the AI Driving Olympics (AI-DO), a new competition focused around AI for self-driving cars. The first edition is going to be at NIPS 2018; the second edition will be at ICRA 2019.

by   -   August 23, 2018


By Adam Conner-Simons | Rachel Gordon

Investigating inside the human body often requires cutting open a patient or swalloing long tubes with built-in cameras. But what if physicians could get a better glimpse in a less expensive, invasive, and time-consuming manner?

by   -   August 9, 2018

A new fabrication process enables the creation of soft robots at the millimeter scale with features on the micrometer scale as shown here with the example of a small soft robotic peacock spider with moving body parts and colored eyes and abdomens. Credit: Wyss Institute at Harvard University

By Benjamin Boettner

Roboticists are envisioning a future in which soft, animal-inspired robots can be safely deployed in difficult-to-access environments, such as inside the human body or in spaces that are too dangerous for humans to work, in which rigid robots cannot currently be used. Centimeter-sized soft robots have been created, but thus far it has not been possible to fabricate multifunctional flexible robots that can move and operate at smaller size scales.

by   -   August 9, 2018

his fully 3D-printed version of the grippers includes “fingernails” on the ends of the fingers to help pick up organisms that are sitting on hard surfaces, as well as mesh extensions between the fingers to keep samples secure. Credit: Wyss Institute at Harvard University

By Lindsay Brownell

The deep ocean – dark, cold, under high pressure, and airless – is notoriously inhospitable to humans, yet it teems with organisms that manage to thrive in its harsh environment. Studying those creatures requires specialized equipment mounted on remotely operated vehicles (ROVs) that can withstand those conditions in order to collect samples. This equipment, designed primarily for the underwater oil and mining industries, is clunky, expensive, and difficult to maneuver with the kind of control needed for interacting with delicate sea life. Picking a delicate sea slug off the ocean floor with these tools is akin to trying to pluck a grape using pruning shears.

by   -   August 9, 2018

In this episode of Robots in Depth, Per Sjöborg speaks with Hans Kimblad about 3D printing metal or MAM, metal adaptive manufacturing.

by   -   August 9, 2018

By John Miller

An earlier version of this post was published on Off the Convex Path. It is reposted here with the author’s permission.

In the last few years, deep learning practitioners have proposed a litany of different sequence models. Although recurrent neural networks were once the tool of choice, now models like the autoregressive Wavenet or the Transformer are replacing RNNs on a diverse set of tasks. In this post, we explore the trade-offs between recurrent and feed-forward models.



Artificial Intelligence and Data Analysis in Salesforce Analytics
September 17, 2018


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