Evolutionary robotics is a sub-field of robotics aimed at developing artificial "organisms" that can improve their capabilities and body configuration in response to their surroundings, just as humans and animals evolve, adapting their skills and appearance over time. A growing number of roboticists have been trying to develop these evolvable robotic systems, leveraging recent artificial intelligence (AI) advances.
To assist humans during their day-to-day activities and successfully complete domestic chores, robots should be able to effectively manipulate the objects we use every day, including utensils and cleaning equipment. Some objects, however, are difficult to grasp and handle for robotic hands, due to their shape, flexibility, or other characteristics.
Robots based on soft materials are often better at replicating the appearance, movements and abilities of both humans and animals. While there are now countless soft robots, many of these are difficult to produce on a large-scale, due to the high cost of their components or their complex fabrication process.
A small team of mechanical engineers at Carnegie Mellon University, working with a colleague from the University of Illinois Urbana-Champaign, has designed and built what they describe as the simplest walking robot ever. They have written a paper describing the ideas they used to build the robot and the factors that have led to its simplicity and have posted it on the arXiv preprint server.
Tubificine worms are segmented worms that are capable of forming entangled blobs that behave as a single organism to adapt to extreme environmental conditions or migrate more efficiently. Individual worms are capable of elongating, entwining an uneven area of terrain and dragging the collective worm ball through a narrow passageway in laboratory experiments.
Unmanned aerial vehicles (UAVs), commonly known as drones, are already used in countless settings to tackle real-world problems. These flying robotic systems can, among other things, help to monitor natural environments, detect fires or other environmental hazards, monitor cities and find survivors of natural disasters.
A robot moves a toy package of butter around a table in the Intelligent Robotics and Vision Lab at The University of Texas at Dallas. With every push, the robot is learning to recognize the object through a new system developed by a team of UT Dallas computer scientists.
The United States military plans to start using thousands of autonomous weapons systems in the next two years in a bid to counter China's growing power, US Deputy Secretary of Defense Kathleen Hicks announced in a speech on Monday.
Coming to a tight spot near you: CLARI, the little, squishable robot that can passively change its shape to squeeze through narrow gaps—with a bit of inspiration from the world of bugs.
Remember when IBM's Deep Blue won against Gary Kasparov at chess in 1996, or Google's AlphaGo crushed the top champion Lee Sedol at Go, a much more complex game, in 2016? These competitions where machines prevailed over human champions are key milestones in the history of artificial intelligence. Now a group of researchers from the University of Zurich and Intel has set a new milestone with the first autonomous system capable of beating human champions at a physical sport: drone racing.
In recent years, roboticists and computer scientists have developed a variety of highly innovative systems that could assist people with physical disabilities, improve their quality of life and aid their rehabilitation. These systems include soft wearable technologies, such as smart assistive gloves.
Most people take getting dressed for granted. But data from the National Center for Health Statistics reveals that 92% of nursing facility residents and at-home care patients require assistance with dressing.
Korean researchers say they have devised a robot that can self-destruct and leave no trace other than an oily puddle.
Scientific exploration of the deep ocean has largely remained inaccessible to most people because of barriers to access due to infrastructure, training, and physical ability requirements for at-sea oceanographic research.
Imagine you want to carry a large, heavy box up a flight of stairs. You might spread your fingers out and lift that box with both hands, then hold it on top of your forearms and balance it against your chest, using your whole body to manipulate the box.