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HRI 2020 Online Day One

HRI2020 has already kicked off with workshops and the Industry Talks Session on April 3, however the first release of videos has only just gone online with the welcome from General Chairs Tony Belpaeme, ID Lab, University of Ghent and James Young, University of Manitoba.

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The Age of A.I. YouTube series

The YouTube originals series “The Age of A.I.” was released in December 2019. If you haven’t already seen it now could be a good time to catch up – with much of the world in enforced or voluntary isolation many of us will be stuck at home with hours to fill. Sit back and marvel at the many incredible, and often heart-warming, applications of AI.

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Human Robot Interaction conference launches online


The 15th Annual ACM/IEEE International Conference on Human Robot Interaction – HRI 2020 – was meant to take place in the city of Cambridge UK. Instead it will be launching online today. You can follow latest happenings on twitter and youtube. Check here for a list of all the papers.

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Robots learning to move like animals


By Xue Bin (Jason) Peng

Whether it’s a dog chasing after a ball, or a monkey swinging through the trees, animals can effortlessly perform an incredibly rich repertoire of agile locomotion skills. But designing controllers that enable legged robots to replicate these agile behaviors can be a very challenging task. The superior agility seen in animals, as compared to robots, might lead one to wonder: can we create more agile robotic controllers with less effort by directly imitating animals?

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COVID-19, robots and us – weekly online discussion

Silicon Valley Robotics and the CITRIS People and Robots Initiative are hosting a weekly “COVID-19, robots and us” online discussion with experts from the robotics and health community on Tuesdays at 7pm (California time – PDT). You can sign-up for the free event here.

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System trains driverless cars in simulation before they hit the road


A simulation system invented at MIT to train driverless cars creates a photorealistic world with infinite steering possibilities, helping the cars learn to navigate a host of worse-case scenarios before cruising down real streets.

By Rob Matheson

A simulation system invented at MIT to train driverless cars creates a photorealistic world with infinite steering possibilities, helping the cars learn to navigate a host of worse-case scenarios before cruising down real streets.  

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This drone can play dodgeball – and win

By Nicola Nosengo

Drones can do many things, but avoiding obstacles is not their strongest suit yet – especially when they move quickly. Although many flying robots are equipped with cameras that can detect obstacles, it typically takes from 20 to 40 milliseconds for the drone to process the image and react. It may seem quick, but it is not enough to avoid a bird or another drone, or even a static obstacle when the drone itself is flying at high speed. This can be a problem when drones are used in unpredictable environments, or when there are many of them flying in the same area.

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Does on-policy data collection fix errors in off-policy reinforcement learning?

Reinforcement learning has seen a great deal of success in solving complex decision making problems ranging from robotics to games to supply chain management to recommender systems. Despite their success, deep reinforcement learning algorithms can be exceptionally difficult to use, due to unstable training, sensitivity to hyperparameters, and generally unpredictable and poorly understood convergence properties. Multiple explanations, and corresponding solutions, have been proposed for improving the stability of such methods, and we have seen good progress over the last few years on these algorithms. In this blog post, we will dive deep into analyzing a central and underexplored reason behind some of the problems with the class of deep RL algorithms based on dynamic programming, which encompass the popular DQN and soft actor-critic (SAC) algorithms – the detrimental connection between data distributions and learned models.

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Showing robots how to do your chores

Roboticists are developing automated robots that can learn new tasks solely by observing humans. At home, you might someday show a domestic robot how to do routine chores.
Image: Christine Daniloff, MIT

By Rob Matheson

Training interactive robots may one day be an easy job for everyone, even those without programming expertise. Roboticists are developing automated robots that can learn new tasks solely by observing humans. At home, you might someday show a domestic robot how to do routine chores. In the workplace, you could train robots like new employees, showing them how to perform many duties.

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The Tentacle Bot

By Leah Burrows

Of all the cool things about octopuses (and there are a lot), their arms may rank among the coolest.

Two-thirds of an octopus’s neurons are in its arms, meaning each arm literally has a mind of its own. Octopus arms can untie knots, open childproof bottles, and wrap around prey of any shape or size. The hundreds of suckers that cover their arms can form strong seals even on rough surfaces underwater.

Imagine if a robot could do all that.

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Driverless shuttles: the latest from two European projects

AIhub | Horizon | Keolis autonomous shuttle
Autonomous vehicles must be well-integrated into public transport systems if they are to take off in Europe’s cities, say researchers. Image credit – Keolis

By Julianna Photopoulos

Jutting out into the sea, the industrial port area of Nordhavn in Denmark’s capital, Copenhagen, is currently being transformed into a futuristic waterfront city district made up of small islets. It’s billed as Scandinavia’s largest metropolitan development project and, when complete, will have living space for 40,000 people and workspace for another 40,000.

At the moment, Nordhavn is only served by a nearby S-train station and bus stops located near the station. There are no buses or trains running within the development area, although there are plans for an elevated metro line, and parking will be discouraged in the new neighbourhood. This is a great opportunity for autonomous vehicles (AVs) to operate as a new public transport solution

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Emergent behavior by minimizing chaos

By Glen Berseth

All living organisms carve out environmental niches within which they can maintain relative predictability amidst the ever-increasing entropy around them (1), (2). Humans, for example, go to great lengths to shield themselves from surprise — we band together in millions to build cities with homes, supplying water, food, gas, and electricity to control the deterioration of our bodies and living spaces amidst heat and cold, wind and storm. The need to discover and maintain such surprise-free equilibria has driven great resourcefulness and skill in organisms across very diverse natural habitats. Motivated by this, we ask: could the motive of preserving order amidst chaos guide the automatic acquisition of useful behaviors in artificial agents?

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Using artificial intelligence to enrich digital maps

An AI model developed at MIT and Qatar Computing Research Institute that uses only satellite imagery to automatically tag road features in digital maps could improve GPS navigation, especially in countries with limited map data.
Image: Google Maps/MIT News

By Rob Matheson

A model invented by researchers at MIT and Qatar Computing Research Institute (QCRI) that uses satellite imagery to tag road features in digital maps could help improve GPS navigation.  

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20+ holiday robot videos

Thanks to all those that sent us their holiday videos. Here’s a selection of 20+ videos to get you into the spirit this season.

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An origami robot for touching virtual reality objects

A group of EPFL researchers have developed a foldable device that can fit in a pocket and can transmit touch stimuli when used in a human-machine interface.

When browsing an e-commerce site on your smartphone, or a music streaming service on your laptop, you can see pictures and hear sound snippets of what you are going to buy. But sometimes it would be great to touch it too – for example to feel the texture of a garment, or the stiffness of a material. The problem is that there are no miniaturized devices that can render touch sensations the way screens and loudspeakers render sight and sound, and that can easily be coupled to a computer or a mobile device.