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Imperial researchers have created drones that can attach sensors to trees to monitor environmental and ecological changes in forests.

Walmart is laying off the robots it had deployed in about 500 stores to keep tabs on what's on and not on the shelves.

A new high-speed amphibious robot inspired by the movements of cockroaches and lizards, developed by Ben-Gurion University of the Negev (BGU) researchers, swims and runs on top of water at high speeds and crawls on difficult terrain.

People tend to accept robots with humanlike characteristics up to a point. Then, things get strangely uncomfortable.

Over the past decade or so, roboticists developed increasingly sophisticated robotic systems that could help humans to complete a variety of tasks, both at home and in other environments. In order to assist users, however, these systems should be able to efficiently navigate and explore their surroundings, without colliding with other objects in their vicinity.

The northern goshawk is a fast, powerful raptor that flies effortlessly through forests. This bird was the design inspiration for the next-generation drone developed by scientists of the Laboratory of Intelligent Systems of EPFL, led by Dario Floreano. They carefully studied the shape of the bird's wings and tail and its flight behavior, and used that information to develop a drone with similar characteristics.

Stanford University researcher Mac Schwager entered the world of penguin counting through a chance meeting at his sister-in-law's wedding in June 2016. There, he learned that Annie Schmidt, a biologist at Point Blue Conservation Science, was seeking a better way to image a large penguin colony in Antarctica. Schwager, who is an assistant professor of aeronautics and astronautics, saw an opportunity to collaborate, given his work on controlling swarms of autonomous flying robots.

The feverish race to produce the shiniest, safest, speediest self-driving car has spilled over into our wheelchairs, scooters, and even golf carts. Recently, there's been movement from land to sea, as marine autonomy stands to change the canals of our cities, with the potential to deliver goods and services and collect waste across our waterways.

A team of researchers is creating mobile robots for military applications that can determine, with or without human intervention, whether wheels or legs are more suitable to travel across terrains. The Defense Advanced Research Projects Agency (DARPA) has partnered with Kiju Lee at Texas A&M University to enhance these robots' ability to self-sufficiently travel through urban military environments.

With a training technique commonly used to teach dogs to sit and stay, Johns Hopkins University computer scientists showed a robot how to teach itself several new tricks, including stacking blocks. With the method, the robot, named Spot, was able to learn in days what typically takes a month.

More than one million American adults use wheelchairs fitted with robot arms to help them perform everyday tasks such as dressing, brushing their teeth, and eating. But the robotic devices now on the market can be hard to control. Removing a food container from a refrigerator or opening a cabinet door can take a long time. And using a robot to feed yourself is even harder because the task requires fine manipulation.

Boston Dynamics announced that it has developed a robot arm for its "Spot" robot and also a charging station. Both will be available for purchase this spring.

Two Princeton researchers, architect Stefana Parascho and engineer Sigrid Adriaenssens, dreamed of using robots to simplify construction, even when building complex forms.

Two Princeton researchers, architect Stefana Parascho and engineer Sigrid Adriaenssens, dreamed of using robots to simplify construction, even when building complex forms.

As robots replace humans in dangerous situations such as search and rescue missions, they need to be able to quickly assess and make decisions—to react and adapt like a human being would. Researchers at the University of Illinois at Urbana-Champaign used a model based on the game Capture the Flag to develop a new take on deep reinforcement learning that helps robots evaluate their next move.