Designing and representing control algorithms is challenging in swarm robotics, where the collective swarm performance depends on interactions between robots and with their environment. The currently available modeling languages, such as UML, cannot fully express these interactions. The Behaviour-Data Relations Modeling Language (BDRML) explicitly represents robot behaviours and data that robots utilise, as well as relationships between them. This allows BDRML to express control algorithms where robots cooperate and share information with each other while interacting with the environment. Here’s the work I presented this week at #IROS2017.
From butterflies that sprout wings to hermit crabs that switch their shells, many animals must adapt their exterior features in order to survive. While humans don’t undergo that kind of metamorphosis, we often try to create functional objects that are similarly adaptive — including our robots.
The ERL Emergency Robots 2017 (#ERLemergency2017) major tournament in Piombino, Italy, gathered 130 participants from 16 universities and companies from 8 European countries. Participating teams designed robots able to bring the first relief to survivors in disaster-response scenarios. The #ERLemergency2017 scenarios were inspired by the Fukushima 2011 nuclear accident. The robotics competition took place from 15-23 September 2017 at Enel’s Torre del Sale, and saw sea, land and air robots collaborating.
As highlighted in a previous post, despite the fact that robotics is increasingly regarded as a ‘Science’, as shown by the launch of new journals such as Science Robotics, reproducibility of experiments is still difficult or entirely lacking.
Summer is not without its annoyances — mosquitos, wasps, and ants, to name a few. As the cool breeze of September pushes us back to work, labs across the country are reconvening tackling nature’s hardest problems. Sometimes forces that seem diametrically opposed come together in beautiful ways, like robotics infused into living organisms.
IBM and MIT today announced that IBM plans to make a 10-year, $240 million investment to create the MIT–IBM Watson AI Lab in partnership with MIT. The lab will carry out fundamental artificial intelligence (AI) research and seek to propel scientific breakthroughs that unlock the potential of AI. The collaboration aims to advance AI hardware, software, and algorithms related to deep learning and other areas; increase AI’s impact on industries, such as health care and cybersecurity; and explore the economic and ethical implications of AI on society. IBM’s $240 million investment in the lab will support research by IBM and MIT scientists.
In this episode, MeiXing Dong talks with Leon Kuperman, CTO of CUJO, about cybersecurity threats and how to guard against them. They discuss how CUJO, a smart hardware firewall, helps protect the home against online threats.
Recent advances in soft robotics have seen the development of soft pneumatic actuators (SPAs) to ensure that all parts of the robot are soft, including the functional parts. These SPAs have traditionally used increased pressure in parts of the actuator to initiate movement, but today a team from NCCR Robotics and RRL, EPFL publish a new kind of SPA, one that uses vacuum, in ScienceRobotics.
Just as drivers observe the rules of the road, most pedestrians follow certain social codes when navigating a hallway or a crowded thoroughfare: Keep to the right, pass on the left, maintain a respectable berth, and be ready to weave or change course to avoid oncoming obstacles while keeping up a steady walking pace.
Even as robots become increasingly common, they remain incredibly difficult to make. From designing and modeling to fabricating and testing, the process is slow and costly: Even one small change can mean days or weeks of rethinking and revising important hardware.
In this episode, Jack Rasiel speaks with Kostas Bekris, who introduces us to tensegrity robotics: a striking robotic design which straddles the boundary between hard and soft robotics. A structure uses tensegrity if it is made of a number of isolated rigid elements which are held in compression by a network of elements that are in tension. Bekris, an Associate Professor of Computer Science, draws from a diverse set of problems to find innovative new ways to control tensegrity robots.
by Anthony King
Stephen Hawking and Elon Musk fear that the robotic revolution may already be underway, but automation isn’t going to take over just yet – first machines will work alongside us.
Robots across the world help out in factories by taking on heavy lifting or repetitive jobs, but the walking, talking kind may soon collaborate with people, thanks to European robotics researchers building prototypes that anticipate human actions.
To make it easier to diagnose and study sleep problems, researchers at MIT and Massachusetts General Hospital have devised a new way to monitor sleep stages without sensors attached to the body. Their device uses an advanced artificial intelligence algorithm to analyze the radio signals around the person and translate those measurements into sleep stages: light, deep, or rapid eye movement (REM).