Tiny robots use sound to self-organize into intelligent groups
Peer-Reviewed Publication
Updates every hour. Last Updated: 10-Sep-2025 04:11 ET (10-Sep-2025 08:11 GMT/UTC)
Animals like bats, whales and insects have long used acoustic signals for communication and navigation. Now, an international team of scientists have taken a page from nature's playbook to model micro-sized robots that use sound waves to coordinate into large swarms that exhibit intelligent-like behavior. The robot groups could one day carry out complex tasks like exploring disaster zones, cleaning up pollution, or performing medical treatments from inside the body, according to team lead Igor Aronson, Huck Chair Professor of Biomedical Engineering, Chemistry, and Mathematics at Penn State.
New research by University at Buffalo and University of Colorado Boulder researchers has uncovered and characterized novel two-dimensional wave patterns — waves that propagate along two directions — whether they are in water or other settings like plasmas and condensed matter.
Medical imaging methods are often affected by background noise. To solve this, some researchers have drawn inspiration from quantum mechanics, which describes how matter and energy behave at the atomic scale. Their studies draw an analogy between how particles vibrate and how pixel intensity spreads out in images and causes noise. Now authors apply the same mathematics to decipher the localization of pixel intensity in images. In this way, they can separate the noise-free “signal” of the anatomical structures in the image from the visual noise of stray pixels.
The German Research Foundation (DFG) is funding LMU scientist Anne-Laure Boulesteix: How can we improve research on statistical methods, asks the biostatistician, and thereby also improve their use?
Here, researchers from Beijing Institute of Nanoenergy and Nanosystems (Chinese Academy of Sciences) and Yonsei University present the latest progress in neuromorphic computing by integrating various neural networks, including SVM, ANN, CNN, RNN, and RC. Starting from the structure of synapses and neurons, they explore how these networks can be combined with neuromorphic devices to replicate more complex brain-like computations. They also propose future development directions for neuromorphic devices, focusing on advancements in their structures, materials, and applications across diverse fields such as vision, touch, hearing, smell, pain and other senses.