Known as the quadrocopter, the aircraft uses the data to create a 3D digital model of its immediate surroundings.
As reported in Pictures of the Future magazine, computer scientists working for Corporate Technology in Princeton and Munich have teamed up with robotics experts from the Massachusetts Institute of Technology near Boston to develop this sophisticated eye in the sky.
The aim of the project is to create a system capable of producing digital models of complex interiors and inspecting inaccessible installations.
For researchers working in artificial intelligence, the development of a system with visual competence remains, even after 50 years, a major challenge. When it comes to looking at the real world, computers are still remarkably primitive. Whereas a young child has no problem distinguishing a tree from an antenna, computers are incapable of reliably matching such images to the relevant object. Research groups from both science and industry are therefore working hard to enhance the visual capability of artificial systems.
At Siemens, researchers are progressively teaching the quadrocopter how to see. The unmanned system measures almost one meter in diameter and is equipped with four rotors. When in flight, it uses lasers to scan its surroundings. Optical sensors and video cameras record every detail.
In a process known as "supervised learning," such systems are initially primed with hundreds of thousands of images, thereby imitating the process whereby a child learns to distinguish, say, a tree from an antenna mast on the basis of having already seen a countless number of objects. Intelligent algorithms then search these images for characteristic features. On this basis, the quadrocopter is able to compile a precise 3D digital model of its surroundings in areas such as baggage-handling facilities, factory buildings, or event venues for the purposes of construction planning or building inspection. In the future the aircraft can fly routine operations to inspect largely inaccessible installations such as wind power plants and electricity pylons.
In other projects at a number of its research and development facilities, Siemens is also developing systems that are able to scan aireal images for complex patterns such as industrial sites, buildings, or roads; examine X-ray images of baggage and shipping containers for suspicious objects; identify and read road signs; and monitor crowds.
Dr. Norbert Aschenbrenner | Siemens InnovationNews
Novel tactile display using computer-controlled surface adhesion
27.11.2019 | Osaka University
Designer lens helps see the big picture
21.11.2019 | King Abdullah University of Science & Technology (KAUST)
With ultracold chemistry, researchers get a first look at exactly what happens during a chemical reaction
The coldest chemical reaction in the known universe took place in what appears to be a chaotic mess of lasers. The appearance deceives: Deep within that...
Abnormal scarring is a serious threat resulting in non-healing chronic wounds or fibrosis. Scars form when fibroblasts, a type of cell of connective tissue, reach wounded skin and deposit plugs of extracellular matrix. Until today, the question about the exact anatomical origin of these fibroblasts has not been answered. In order to find potential ways of influencing the scarring process, the team of Dr. Yuval Rinkevich, Group Leader for Regenerative Biology at the Institute of Lung Biology and Disease at Helmholtz Zentrum München, aimed to finally find an answer. As it was already known that all scars derive from a fibroblast lineage expressing the Engrailed-1 gene - a lineage not only present in skin, but also in fascia - the researchers intentionally tried to understand whether or not fascia might be the origin of fibroblasts.
Fibroblasts kit - ready to heal wounds
Research from a leading international expert on the health of the Great Lakes suggests that the growing intensity and scale of pollution from plastics poses serious risks to human health and will continue to have profound consequences on the ecosystem.
In an article published this month in the Journal of Waste Resources and Recycling, Gail Krantzberg, a professor in the Booth School of Engineering Practice...
Conventional light microscopes cannot distinguish structures when they are separated by a distance smaller than, roughly, the wavelength of light. Superresolution microscopy, developed since the 1980s, lifts this limitation, using fluorescent moieties. Scientists at the Max Planck Institute for Polymer Research have now discovered that graphene nano-molecules can be used to improve this microscopy technique. These graphene nano-molecules offer a number of substantial advantages over the materials previously used, making superresolution microscopy even more versatile.
Microscopy is an important investigation method, in physics, biology, medicine, and many other sciences. However, it has one disadvantage: its resolution is...
03.12.2019 | Event News
15.11.2019 | Event News
15.11.2019 | Event News
05.12.2019 | Life Sciences
05.12.2019 | Life Sciences
05.12.2019 | Materials Sciences