Jet engines can have up to 25,000 individual parts, making regular maintenance a tedious task that can take over a month per engine. Many components are located deep inside the engine and cannot be inspected without taking the machine apart, adding time and costs to maintenance. This problem is not only confined to jet engines, either; many complicated, expensive machines like construction equipment, generators, and scientific instruments require large investments of time and money to inspect and maintain.
Work by I. Slavkov, D. Carrillo-Zapata, N. Carranza, X. Diego, F. Jansson, J. Kaandorp, S. Hauert, J. Sharpe
Our work published today in Science Robotics describes how we grow fully self-organised shapes using a swarm of 300 coin-sized robots. The work was led by James Sharpe at EMBL and the Centre for Genomic Regulation (CRG) in Barcelona – together with my team at the Bristol Robotics Laboratory and University of Bristol.
That’s right! You better not run, you better not hide, you better watch out for brand new robot holiday videos on Robohub! Drop your submissions down our chimney at firstname.lastname@example.org and share the spirit of the season.
In a world first, an undersea robot has dispersed microscopic baby corals (coral larvae) to help scientists working to repopulate parts of the Great Barrier Reef during this year’s mass coral spawning event.
Six weeks after winning the Great Barrier Reef Foundation’s $300,000 Out of the Blue Box Reef Innovation Challenge, Southern Cross University’s Professor Peter Harrison and QUT’s Professor Matthew Dunbabin trialled the ground-breaking initiative on Vlasoff Reef, near Cairns in north Queensland.
A research team from the University of Zurich and EPFL has developed a new drone that can retract its propeller arms in flight and make itself small to fit through narrow gaps and holes. This is particularly useful when searching for victims of natural disasters.
by Steve Gillman
Every year 7 million hectares of forest are cut down, chipping away at the 485 gigatonnes of carbon dioxide (CO2) stored in trees around the world, but low-cost drones and new satellite imaging could soon protect these carbon stocks and help developing countries get paid for protecting their trees.
Machine learning algorithms now underlie much of the software we use, helping to personalize our news feeds and finish our thoughts before we’re done typing. But as artificial intelligence becomes further embedded in daily life, expectations have risen. Before autonomous systems fully gain our confidence, we need to know they are reliable in most situations and can withstand outside interference; in engineering terms, that they are robust. We also need to understand the reasoning behind their decisions; that they are interpretable.
By Tuomas Haarnoja, Vitchyr Pong, Kristian Hartikainen, Aurick Zhou, Murtaza Dalal, and Sergey Levine
We are announcing the release of our state-of-the-art off-policy model-free reinforcement learning algorithm, soft actor-critic (SAC). This algorithm has been developed jointly at UC Berkeley and Google Brain, and we have been using it internally for our robotics experiment. Soft actor-critic is, to our knowledge, one of the most efficient model-free algorithms available today, making it especially well-suited for real-world robotic learning. In this post, we will benchmark SAC against state-of-the-art model-free RL algorithms and showcase a spectrum of real-world robot examples, ranging from manipulation to locomotion. We also release our implementation of SAC, which is particularly designed for real-world robotic systems.
Elowan is a cybernetic lifeform, a plant in direct dialogue with a machine. Using its own internal electrical signals, the plant is interfaced with a robotic extension that drives it toward light.
Plants are electrically active systems. They get bio-electrochemically excited and conduct these signals between tissues and organs. Such electrical signals are produced in response to changes in light, gravity, mechanical stimulation, temperature, wounding, and other environmental conditions.
“The Laughing Room,” an interactive art installation by author, illustrator, and MIT graduate student Jonathan “Jonny” Sun, looks like a typical living room: couches, armchairs, coffee table, soft lighting. This cozy scene, however, sits in a glass-enclosed space, flanked by bright lights and a microphone, with a bank of laptops and a video camera positioned across the room. People wander in, take a seat, begin chatting. After a pause in the conversation, a riot of canned laughter rings out, prompting genuine giggles from the group.
By Chelsea Finn∗, Frederik Ebert∗, Sudeep Dasari, Annie Xie, Alex Lee, and Sergey Levine
With very little explicit supervision and feedback, humans are able to learn a wide range of motor skills by simply interacting with and observing the world through their senses. While there has been significant progress towards building machines that can learn complex skills and learn based on raw sensory information such as image pixels, acquiring large and diverse repertoires of general skills remains an open challenge. Our goal is to build a generalist: a robot that can perform many different tasks, like arranging objects, picking up toys, and folding towels, and can do so with many different objects in the real world without re-learning for each object or task.
The empty frames hanging inside the Isabella Stewart Gardner Museum serve as a tangible reminder of the world’s biggest unsolved art heist. While the original masterpieces may never be recovered, a team from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) might be able to help, with a new system aimed at designing reproductions of paintings.
Why is a Robotics Flagship needed?
Robotics is a solid technological field, with important market opportunities. Europe contributed significantly to the growth of knowledge in this field and it is competitive, both in science and in industry. A European investment in robotics, with a long-term vision on the scale of a FET-Flagship, can take advantage of European competitiveness to boost industry and promote the robotics market expected across many service sectors. A public European initiative can also guarantee responsible robotics progress that produces beneficial socio-economic impacts, sustainable technological developments, welfare and jobs.
The European Robotics Week (ERW) is achieving a major success with around 1200 interactive robotics related events across Europe, showing how robots will impact the way we work, live, and learn both now and in the future. Every year the ERW changes the central event and hosts an eco-system of various engaging activities in the chosen location. From 16 to 18 November, Augsburg has been in the spotlight, hosting the Central event of the European Robotics Week 2018 with 1,500 visitors coming to the exhibition over the three days.
A couple of months ago I interviewed Joel Esposito about the state of robotics education for the ROS Developers Podcast #21. On that podcast, Joel talks about his research on how robotics is taught around the world. He identifies a set of common robotics subjects that need to be explained in order to make students know about robotics, and a list of resources that people are using to teach them. But most important, he points out the importance of practicing with robots what students learn.