A team of researchers has unveiled a cutting-edge Amphibious Robotic Dog capable of roving across both land and water with remarkable efficiency. The study, published in Bioinspiration and Biometrics, was inspired by mammals' ability to move through water as well as on land.
A human clearing junk out of an attic can often guess the contents of a box simply by picking it up and giving it a shake, without the need to see what's inside. Researchers from MIT, Amazon Robotics, and the University of British Columbia have taught robots to do something similar.
MIT engineers are getting in on the robotic ping pong game with a powerful, lightweight design that returns shots with high-speed precision.
Researchers have developed an "Intelligent Autonomous Wiping and UV-C Disinfection Robot" capable of automating hospital disinfection processes.
France's armed forces are on schedule to develop battle-ready robots by 2040, according to participants in a test bringing together the military with engineers, researchers and defense contractors.
The hospitality industry can leverage the gender characteristics of service robots to influence customers' decisions, according to new research from a team in the Penn State School of Hospitality Management.
Imagine AI-controlled robots that organize themselves into different groups, or across groups—and that reorganize themselves and make new plans when needed. This kind of flexibility can enable robots to effectively solve different types of tasks as a team.
Researchers at Northwestern University and Israel's Tel Aviv University have overcome a major barrier to achieving a low-cost solution for advanced robotic touch. The authors argue that the problem that has been lurking in the margins of many papers about touch sensors lies in the robotic skin itself.
Digital twins are a rapidly advancing area in engineering, going beyond static models to continuously receive data from the physical world and make predictions that go on to affect that reality. They have applications in areas such as energy systems, manufacturing and medicine. U-M's Automotive Research Center (ARC) uses them to help design, test and control autonomous off-road vehicles that operate in human-led teams.
Delivery robots made by companies such as Starship Technologies and Kiwibot autonomously make their way along city streets and through neighborhoods.
Recent advances in robotics and machine learning have enabled the automation of many real-world tasks, including various manufacturing and industrial processes. Among other applications, robotic and artificial intelligence (AI) systems have been successfully used to automate some steps in manufacturing clothes.
Many robotic applications rely on robotic arms or hands to handle different types of objects. Estimating the pose of such hand-held objects is an important yet challenging task in robotics, computer vision and even in augmented reality (AR) applications. A promising direction is to utilize multi-modal data, such as color (RGB) and depth (D) images. With the increasing availability of 3D sensors, many machine learning approaches have emerged to leverage this technique.
Trees, vegetation, rocks, unpredictable terrain and the lack of clearly defined roads—or roads at all—won't stop an autonomous, off-road vehicle developed by researchers at Carnegie Mellon University's Robotics Institute.
Fish are masters of coordinated motion. Schools of fish have no leader, yet individuals manage to stay in formation, avoid collisions, and respond with liquid flexibility to changes in their environment. Reproducing this combination of robustness and flexibility has been a long-standing challenge for human-engineered systems like robots.
For delivery robots, not all sidewalks are created equal—some are uneven or clogged with people and bus shelters—so researchers at Cornell Tech developed a "robotability score" and rated every street in New York City on how hospitable it would be to robots.