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Category: robotics/AI – Page 414

Fraunhofer researchers developed an easy-to-operate, unmanned watercraft that autonomously surveys bodies of water both above and below the surface and produces corresponding 3D maps.

The unmanned watercraft uses its GPS, acceleration and angular rate sensors, and a Doppler velocity log (DVL) sensor to incrementally feel its way along the bottom of the body of water. In combination with mapping software, laser scanners, and cameras enable the device to reconstruct high-precision 3D models of the surroundings above water. A multi-beam sonar integrated into the sensor system is used for underwater mapping and creating a complete 3D model of the bed.

“Our navigation system is semi-automatic in that the user only needs to specify the area to be mapped. The surveying process itself is fully automatic, and data evaluation is carried out with just a few clicks of the mouse. We developed the software modules required for the mapping and autonomous piloting,” explains Dr. Janko Petereit, a scientist at Fraunhofer IOSB.

During the journey, it autonomously avoids obstacles detected by the laser scanner and sonar and generates a 3D model in real time for navigation purposes, including dynamic objects such as moving vessels.

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In a revolutionary scientific endeavor, researchers are using 5,000 miniature robots perched atop a mountaintop telescope to peer an astonishing 11 billion years into the past. This cutting-edge instrument, known as the Dark Energy Spectroscopic Instrument (DESI), is capturing light from distant objects in space, allowing scientists from the Lawrence Berkeley National Laboratory to map our cosmos as it was in its infancy and trace its evolution to the present day.

Why is this so important? Understanding how our universe has evolved is intrinsically linked to predicting its ultimate fate and unraveling one of the biggest mysteries in physics: dark energy. This enigmatic force is causing our universe to expand at an ever-increasing rate, and DESI is providing us with unprecedented insights into its effects over the past 11 billion years.

DESI has created the largest and most precise 3D map of our cosmos ever constructed, enabling scientists to measure the expansion history of the young universe with a precision better than 1 percent for the first time. This unparalleled view of the universe’s evolution is shedding light on the interplay between matter, dark matter, and dark energy in shaping the cosmos.

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Machine learning techniques may appear ill-suited for application in fields that prioritize rigor and deep understanding; however, they have recently found unexpected uses in theoretical physics and pure mathematics. In this Perspective, Gukov, Halverson and Ruehle have discussed rigorous applications of machine learning to theoretical physics and pure mathematics.

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From sensetime, shanghai #AI lab, & tsinghua U

InternLM-XComposer2-4KHD

A Pioneering Large Vision-Language Model Handling Resolutions from 336 Pixels to 4K HD https://huggingface.co/papers/2404.

The Large Vision-Language Model (LVLM) field has seen significant advancements, yet its progression…

Join the discussion on this paper page.

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“We need to accelerate and intensify efforts to recover Antarctic meteorites,” said Dr. Harry Zekollari. “The loss of Antarctic meteorites is much like the loss of data that scientists glean from ice cores collected from vanishing glaciers – once they disappear, so do some of the secrets of the universe.”

How can climate change effect the search for meteorites in Antarctica? This is what a recent study published in Nature Climate Change hopes to address as an international team of researchers investigated how melting snow and ice could prevent successful identification of meteorites, of which approximately 60 percent of all meteorites retrieved on Earth have been found in Antarctica. This study holds the potential to help scientists, climate change activists, and legislators better understand the impacts of climate change on science, as meteorites are crucial for gaining greater insight into the formation and evolution of the solar system and beyond.

With a combination of climate models, satellite observations, and artificial intelligence, the researchers estimate that at current rates, they will lose the ability to identify approximately 5,000 meteorites annually, with approximately 24 percent being lost by 2050 and potentially 76 percent by 2100.

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