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Categories: Engineering: Robotics Research, Mathematics: Modeling

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Have you ever wondered how insects are able to go so far beyond their home and still find their way? The answer to this question is not only relevant to biology but also to making the AI for tiny, autonomous robots. Drone-researchers felt inspired by biological findings on how ants visually recognize their environment and combine it with counting their steps in order to get safely back home. They have used these insights to create an insect-inspired autonomous navigation strategy for tiny, lightweight robots. It allows such robots to come back home after long trajectories, while requiring extremely little computation and memory (0.65 kiloByte per 100 m). In the future, tiny autonomous robots could find a wide range of uses, from monitoring stock in warehouses to finding gas leaks in industrial sites.

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A new technique estimates the reliability of a self-supervised foundation model, like those that power ChatGPT, without the need to know what task that model will be deployed on later.

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Researchers are training neural networks to make decisions more like humans would. This science of human decision-making is only just being applied to machine learning, but developing a neural network even closer to the actual human brain may make it more reliable, according to the researchers.

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A new technique enables huge machine-learning models to efficiently generate more accurate quantifications of their uncertainty about certain predictions. This could help practitioners determine whether to trust the model when it is deployed in real-world settings.

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Scientists have developed a tiny 'claw machine' that is able to pick up and drop a marble-sized ball in response to exposure to chemical vapors. The findings point to a technique that can enable soft actuators--the parts of a machine that make it move--to perform multiple tasks without the need for additional costly materials. While existing soft actuators can be 'one-trick ponies' restricted to one type of movement, this novel composite film contorts itself in different ways depending on the vapor that it is exposed to.

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Researchers have developed a groundbreaking method for analysing heart MRI scans with the help of artificial intelligence, which could save valuable time and resources, as well as improve care for patients.

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Engineers have trained a humanoid robot to perform a variety of expressive movements, from simple dance routines to gestures like waving, high-fiving and hugging, all while maintaining a steady gait on diverse terrains. This work marks a step towards building robots that perform more complex and human-like motions.

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Engineers have developed a new soft, flexible device that makes robots move by expanding and contracting -- just like a human muscle. To demonstrate their new device, called an actuator, the researchers used it to create a cylindrical, worm-like soft robot and an artificial bicep. In experiments, the cylindrical soft robot navigated the tight, hairpin curves of a narrow pipe-like environment, and the bicep was able to lift a 500-gram weight 5,000 times in a row without failing.

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Scientists developed and tested new artificial intelligence (AI) tools tailored to digital pathology--a rapidly growing field that uses high-resolution digital images created from tissue samples to help diagnose disease and guide treatment.

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Researchers have developed an easy-to-use tool that enables someone to perform complicated statistical analyses on tabular data using just a few keystrokes. Their method combines probabilistic AI models with the programming language SQL to provide faster and more accurate results than other methods.

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An artificial intelligence (AI) model that can estimate with high accuracy a person's lung function just by using a chest radiograph has been successfully developed.

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Drosophila -- known as fruit flies -- are a valuable model for human heart pathophysiology, including cardiac aging and cardiomyopathy. However, a choke point in evaluating fruit fly hearts is the need for human intervention to measure the heart at moments of its largest expansion or its greatest contraction to calculate cardiac dynamics. Researchers now show a way to significantly cut the time needed for that analysis while utilizing more of the heart region, using deep learning and high-speed video microscopy.

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Physicists have developed a computer program incorporating machine learning that could help identify blobs of plasma in outer space known as plasmoids. In a novel twist, the program has been trained using simulated data.

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Everyday clothing may soon be able to capture and record body movements according to new research.

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Physicists have made a significant breakthrough in solar cell technology by developing a new analytical model that improves the understanding and efficiency of thin-film photovoltaic (PV) devices.

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With a new surgical intervention and neuroprosthetic interface, researchers restored a natural walking gait in people with amputations below the knee. Seven patients were able to walk faster, avoid obstacles, and climb stairs more naturally than people with a traditional amputation.

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Computer scientists have invented a camera mechanism that improves how robots see and react to the world around them. Inspired by how the human eye works, their innovative camera system mimics the tiny involuntary movements used by the eye to maintain clear and stable vision over time.

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Researchers have developed nanorobots that kill cancer cells in mice. The robot's weapon is hidden in a nanostructure and is exposed only in the tumour microenvironment, sparing healthy cells.

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AI model finds the cancer clues at lightning speed. Researchers have developed an AI model that increases the potential for detecting cancer through sugar analyses. The AI model is faster and better at finding abnormalities than the current semi-manual method.

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Researchers have developed a novel deep learning algorithm that outperformed existing computer-based osteoporosis risk prediction methods, potentially leading to earlier diagnoses and better outcomes for patients with osteoporosis risk.