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Categories: Engineering: Robotics Research

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     (via sciencedaily.com)     Original source 

A new machine-learning technique can train and control a reconfigurable soft robot that can dynamically change its shape to complete a task. The researchers also built a simulator that can evaluate control algorithms for shape-shifting soft robots.

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Researchers have developed a robotic feeding system that uses computer vision, machine learning and multimodal sensing to safely feed people with severe mobility limitations, including those with spinal cord injuries, cerebral palsy and multiple sclerosis.

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Walking and running is notoriously difficult to recreate in robots. Now, a group of researchers has overcome some of these challenges by creating an innovative method that employs central pattern generators -- neural circuits located in the spinal cord that generate rhythmic patterns of muscle activity -- with deep reinforcement learning. The method not only imitates walking and running motions but also generates movements for frequencies where motion data is absent, enables smooth transition movements from walking to running, and allows for adapting to environments with unstable surfaces.

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When old food packaging, discarded children's toys and other mismanaged plastic waste break down into microplastics, they become even harder to clean up from oceans and waterways. These tiny bits of plastic also attract bacteria, including those that cause disease. Researchers describe swarms of microscale robots (microrobots) that captured bits of plastic and bacteria from water. Afterward, the bots were decontaminated and reused.

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Engineers created a catapillar-shaped robot that splits into segments and reassembles, hauls cargo, and crawls through twisting courses.

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A stretchy electronic skin could equip robots and other devices with the same softness and touch sensitivity as human skin, opening up new possibilities to perform tasks that require a great deal of precision and control of force.

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New algorithm encourages robots to move more randomly to collect more diverse data for learning. In tests, robots started with no knowledge and then learned and correctly performed tasks within a single attempt. New model could improve safety and practicality of self-driving cars, delivery drones and more.

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Common household products containing nanoparticles -- grains of engineered material so miniscule they are invisible to the eye -- could be contributing to a new form of indoor air pollution, according to a new study.

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A four-legged robot trained with machine learning has learned to avoid falls by spontaneously switching between walking, trotting, and pronking -- a milestone for roboticists as well as biologists interested in animal locomotion.

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Scientists have developed a smart, reusable adhesive more than ten times stronger than a gecko's feet adhesion, pointing the way for development of reusable superglue and grippers capable of holding heavy weights across rough and smooth surfaces. The research team found a way to maximize the adhesion of the smart adhesives by using shape-memory polymers, which can stick and detach easily when needed simply by heating them. This smart adhesive can support extremely heavy weights, opening new possibilities for robotic grippers that allow humans to scale walls effortlessly, or climbing robots that can cling onto ceilings for survey or repair applications.

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Researchers have developed tiny, flexible devices that can wrap around individual nerve fibers without damaging them. The researchers combined flexible electronics and soft robotics techniques to develop the devices, which could be used for the diagnosis and treatment of a range of disorders, including epilepsy and chronic pain, or the control of prosthetic limbs.

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For most human proteins, there are no small molecules known to bind them chemically (so called 'ligands'). Ligands frequently represent important starting points for drug development but this knowledge gap critically hampers the development of novel medicines. Researchers at CeMM, in a collaboration with Pfizer, have now leveraged and scaled a method to measure the binding activity of hundreds of small molecules against thousands of human proteins. This large-scale study revealed tens of thousands of ligand-protein interactions that can now be explored for the development of chemical tools and therapeutics. Moreover, powered by machine learning and artificial intelligence, it allows unbiased predictions of how small molecules interact with all proteins present in living human cells. These groundbreaking results have been published in the journal Science (DOI: 10.1126/science.adk5864), and all generated data and models are freely available for the scientific community.

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Robotics engineers have worked for decades and invested many millions of research dollars in attempts to create a robot that can walk or run as well as an animal. And yet, it remains the case that many animals are capable of feats that would be impossible for robots that exist today.

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A new robotic suction cup which can grasp rough, curved and heavy stone, has been developed by scientists.

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Researchers are targeting the next generation of soft actuators and robots with an elastomer-based ink for 3D printing objects with locally changing mechanical properties, eliminating the need for cumbersome mechanical joints.

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Soft skin coverings and touch sensors have emerged as a promising feature for robots that are both safer and more intuitive for human interaction, but they are expensive and difficult to make. A recent study demonstrates that soft skin pads doubling as sensors made from thermoplastic urethane can be efficiently manufactured using 3D printers.

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More than five million central lines are placed in patients who need prolonged drug delivery, such as those undergoing cancer treatments, in the United States every year, yet the common procedure can lead to a bevy of complications in almost a million of those cases. Researchers developed a robotic simulation training program to provide trainee physicians with more practice on the procedure. A year after deploying the program the team found that all complication types -- mechanical issues, infections and blood clots -- were significantly lower.

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Star Trek's Holodeck is no longer just science fiction. Using AI, engineers have created a tool that can generate 3D environments, prompted by everyday language.

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Engineers designed modular, spring-like devices to maximize the work of live muscle fibers so they can be harnessed to power biohybrid robots.

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Researchers gave nanorobots a trait called adaptive time delay, which allows them to better work together.