A new imaging technique makes it possible to precisely digitize clear objects and their surroundings, an achievement that has eluded current state-of-the-art 3D rendering methods. The ability to ...

In order to see and then grasp objects, robots typically utilize depth-sensing cameras. And while such cameras may be thwarted by transparent or shiny objects, scientists at Carnegie Mellon University ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Optical sensors such as cameras and lidar are a fundamental part of ...

Toyohashi University of Technology discovered that when people judge the thickness of an object, objects with glass-like transparent optical properties are perceived to be flatter than they actually ...

The SA1E-X transparent models feature a coaxial optic and narrow beam to ensure stable detection. They can reliably detect objects with irregular surfaces and are not affected by angle, inclination or ...

Robots have got pretty good at picking up objects. But give them something shiny or clear, and the poor droids will likely lose their grip. Not ideal if you want a kitchen robot that can slice you a ...

In biological microscopy and X-ray imaging, many transparent objects or structures are difficult to observe. Due to their low absorption of light, the usual intensity measurements don't work. Instead, ...

Kitchen robots are a popular vision of the future, but if a robot of today tries to grasp a kitchen staple such as a clear measuring cup or a shiny knife, it likely won't be able to. Transparent and ...

Picking up transparent objects is hard when you’re a robot. Many of the traditional cameras and sensors just can’t get a good enough view to tell the grasper where to go. The light from infrared ...

You might not see most objects in near-total darkness, but AI can. MIT scientists have developed a technique that uses a deep neural network to spot objects in extremely low light. The team trained ...

The research team led by Masakazu Ohara, graduate student of the Department of Computer Science and Engineering at Toyohashi University of Technology (student in the Leading Program doctoral program); ...