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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.

2 Department of Neurobiology, Duke University, Durham, NC, United States.

3Center for Bioelectric Interfaces of the Institute for Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russia.

4Department of Information and Internet Technologies of Digital Health Institute, I.M. Sechenov First Moscow State Medical University, Moscow, Russia.

The technology can also be used to devise a range of advanced sensors for everyday use and to advance science. Twamley’s lab uses levitating materials to build oscillators, which can be used to develop ultra-sensitive sensors. Making these oscillators work without using external energy sources can make them easier to deploy, and this is what the research team at OIST set out to do. What they faced was a series of challenges.

The device that OIST researchers aimed for was a ‘frictionless’ platform. However, the system would lose energy over time without an external power source. This is known as ‘eddy damping’ since external forces make an oscillating system lose energy.

The other hurdle to overcome would be minimizing the system’s kinetic energy. This is necessary since it can help improve the system’s sensitivity if it were to be used as a sensor. If the kinetic motion can be further cooled to the quantum realm, it could also open up possibilities of more precision measurements.

In a global research effort, scientists have uncovered a relationship between metabolism problems in the brain and a range of neuropsychiatric and neurodegenerative disorders, from autism to Alzheimer’s disease and more.

Despite their diverse symptoms, these conditions – as well as depression, epilepsy, schizophrenia, intellectual disability, and bipolar disorder – all involve a degree of cognitive impairment and often share genetic or metabolic features, hinting at a common biological basis.

The extensive collaboration by the International Brain pH Project Consortium, involving 131 scientists from 105 labs in seven countries, identified changes in brain acidity and lactate levels in animals as key signs of this metabolic dysfunction.

A non-radical proximity labelling platform — BAP-seq — is presented that uses subcellular-localized BS2 esterase to convert unreactive enol-based probes into highly reactive acid chlorides in situ to label nearby RNAs. When paired with click-handle-mediated enrichment and sequencing, this chemistry enables high-resolution spatial mapping of RNAs across subcellular compartments.