At UC Berkeley, researchers in Sergey Levine's Robotic AI and Learning Lab eyed a table where a tower of 39 Jenga blocks stood perfectly stacked. Then a white-and-black robot, its single limb doubled over like a hunched-over giraffe, zoomed toward the tower, brandishing a black leather whip. Through what might have seemed to a casual viewer like a miracle of physics, the whip struck in precisely the right spot to send a single block flying from the stack while the rest of the tower remained structurally sound.
Modular robots built by Dartmouth researchers are finding their feet outdoors. Engineered to assemble into structures that best suit the task at hand, the robots are pieced together from cube-shaped robotic blocks that combine rigid rods and soft, stretchy strings whose tension can be adjusted to deform the blocks and control their shape.
Robots come in a vast array of shapes and sizes. By definition, they're machines that perform automatic tasks and can be operated by humans, but sometimes work autonomously—without human help.
Researchers from Scottish universities have developed an innovative way to breathe new life into outdated robot pets and toys using augmented reality technology.
While working at NASA in 2003, Dr. Robert Ambrose, director of the Robotics and Automation Design Lab (RAD Lab), designed a robot with no fixed top or bottom. A perfect sphere, the RoboBall could not flip over, and its shape promised access to places wheeled or legged machines could not reach—from the deepest lunar crater to the uneven sands of a beach.
Nature, particularly humans and other animals, has always been among the primary sources of inspiration for roboticists. In fact, most existing robots physically resemble specific animals and/or are engineered to tackle tasks by emulating the actions, movements and behaviors of specific species.
You might have noticed that humanoid robots are having a bit of a moment. From Tesla's Optimus to Figure AI's Figure 02, these machines are no longer just science fiction—they're walking, and in some cases, cartwheeling into the real world.
In a world where automation is advancing by leaps and bounds, collaboration between robots is no longer science fiction. Imagine a warehouse where dozens of machines transport goods without colliding, a restaurant where robots serve dishes to the correct tables, or a factory where robot teams instantly adjust their tasks according to demand.
Most existing robots designed to move on the ground rely on either wheels or legs, as opposed to a combination of the two. Yet robots that can seamlessly switch between wheeled and legged locomotion could be highly advantageous, as they could move more efficiently on a wider range of terrains, which could in turn contribute to the successful completion of missions.
When designing new robots, engineers often look to nature for inspiration. They base their robots on the designs and behaviors of snakes, fish, humans, and more, such as sea slugs, whose feeding behaviors have been studied in recent research by the Carnegie Mellon University Biohybrid and Organic Robotics group under the direction of Vickie Webster-Wood, associate professor of mechanical engineering.
A new AI-powered tool created by researchers at Carnegie Mellon University's School of Computer Science could change the way we manufacture and build things.
Science frequently draws inspiration from the natural world. After all, nature has had billions of years to perfect its systems and processes. Taking their cue from mollusk catch muscles, researchers have developed a low-voltage, muscle-like actuator that can help insect-scale soft robots to crawl, swim and jump autonomously in real-world settings. Their work solves a long-standing challenge in soft robotics: enabling tiny robots to move on their own without sacrificing power or precision.
To effectively tackle a variety of real-world tasks, robots should be able to reliably grasp objects of different shapes, textures and sizes, without dropping them in undesired locations. Conventional approaches to enhancing the ability of robots to grasp objects work by tightening the grip of a robotic hand to prevent objects from slipping.
Modern robotic systems—in drones or autonomous vehicles, for example—use a variety of sensors, ranging from cameras and accelerometers to GPS modules. To date, their correct integration has required expert knowledge and time-consuming calibration.
Animals like bats, whales and insects have long used acoustic signals for communication and navigation. Now, an international team of scientists has taken a page from nature's playbook to model micro-sized robots that use sound waves to coordinate into large swarms that exhibit intelligent-like behavior.