All posts by Robotics News - Robot News, Robotics, Robots, Robotics Sciences

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Insect-inspired robot tracks odors even with only one working ‘antenna’

A collaborative research group has developed a bio-inspired robotic system based on insect behavior which can locate odor sources both indoors and outdoors with consistent accuracy, even if one of its two sensors fails. The team includes Assistant Professor Shigaki Shunsuke of the National Institute of Informatics (NII), Professor Kurabayashi Daisuke of the School of Engineering at Science Tokyo, and Associate Professor Owaki Dai of the Graduate School of Engineering at Tohoku University.

Simple motor networks mimic human muscle behavior under increasing load

Scientists have developed a network of mechanical motors that mimic the molecular machinery underpinning human muscle contraction. The University of Bristol-led findings, published in the Journal of the Royal Society Interface this week, could open new possibilities for artificial muscles in robotics.

How Chicago robot tutors are teaching SEL effectively, without pretending to be human

In a crowded fourth-grade classroom in Chicago, a new kind of tutor is shaping how children learn about empathy, conflict, and problem-solving. These robots aren't programmed to act like friendly classmates with invented emotions and backstories. Instead, they speak plainly, without pretense or fiction, and the results will attract educators' attention across the country.

Wind-powered robot could enable long-term exploration of hostile environments

Researchers at Cranfield University have created WANDER-bot, a low-cost, 3D-printed robot that is powered by wind energy. Designed to spend long durations in hostile, windy environments such as certain deserts, polar regions or even other planets, WANDER-bot doesn't need a battery to power movement, enabling longer operations without having to pause and recharge.

Humanoid robot learns impressive tennis skills from imperfect human motion

Roboticists have struggled to get humanoid robots to effectively replicate athletic sports skills, such as those needed for tennis. These sports require highly dynamic motion, quick reactions, and high precision that robots are not usually equipped to handle. Past research attempted to use kinematic data and video-based extraction of human motion data, but these approaches were complex and often physically infeasible. Some robots have been trained to play sports like table tennis or football, but with limited agility and realism.

Swimming robot propelled by lab-grown muscle hits record speed

NUS researchers have developed a platform that lets lab-grown muscle tissues train themselves to record-breaking strength, with no external stimulation required. By mechanically coupling two muscle tissues so they continuously pull against each other, their own natural contractions become a round-the-clock workout. The resulting muscles powered OstraBot, an ostraciiform (a type of fish locomotion) swimming robot that reached 467 millimeters per minute—the fastest speed reported for any skeletal muscle-driven biohybrid robot.

Generative AI improves a wireless vision system that sees through obstructions

MIT researchers have spent more than a decade studying techniques that enable robots to find and manipulate hidden objects by "seeing" through obstacles. Their methods utilize surface-penetrating wireless signals that reflect off concealed items. Now, the researchers are leveraging generative artificial intelligence models to overcome a longstanding bottleneck that limited the precision of prior approaches.

Sheepdogs reveal a better way to guide robot swarms

Sheepdogs, bred to control large groups of sheep in open fields, have demonstrated their skills in competitions dating back to the 1870s. In these contests, a handler directs a trained dog with whistle signals to guide a small group of sheep across a field and sometimes split the flock cleanly into two groups. But sheep do not always cooperate.

Compostable robot endures over 1 million uses before becoming plant food

The rapid proliferation of robots and electronic devices is placing the world under a new and growing environmental burden. According to the United Nations Institute for Training and Research (UNITAR), global electronic waste (e-waste) reached approximately 62 million metric tons in 2022, a significant portion of which was neither properly collected nor recycled but instead landfilled or incinerated.

Autonomous navigation of microrobots in complex flows demonstrated for the first time

For the first time, researchers at Leipzig University have shown that tiny synthetic microswimmers can perceive their surroundings directly through their own body shape and autonomously adapt to rapidly changing fluid flows. The study, now published in Science Advances, establishes a new paradigm for autonomous microsystems whose control functions reliably in challenging environments where conventional sensors fail. This opens up new prospects for autonomous medical microrobots, for example for the targeted delivery of medication in the bloodstream.

4D printing technology uses waste sulfur to enable self-actuating soft robots

A joint research team led by Dr. Dong-Gyun Kim of the Korea Research Institute of Chemical Technology (KRICT), Professor Jeong Jae Wie of Hanyang University, and Professor Yong Seok Kim of Sejong University report the world's first 4D printing technology based on sulfur-rich polymers that respond to heat, light, and magnetic fields. The study was published in Advanced Materials.

New chip lets robots see in 4D by tracking distance and speed simultaneously

Current vision systems for robots and drones rely on 3D sensors that, although powerful, do not always keep up with the fast-paced, unpredictable movement of the real world. These systems often struggle to measure speed instantly or are too bulky and expensive for everyday use. Now, in a paper published in the journal Nature, scientists report how they have developed a 4D imaging sensor on a chip that creates 3D maps of an environment while simultaneously tracking the speed of moving objects.
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