Connect with us

Published

on

Researchers have created a novel electronic “skin” that could let robots experience a sense of touch. This low-cost, gelatin-based material is highly flexible and durable and can be molded over a robot hand. Equipped with electrodes, the skin detects pressure, temperature changes, and even sharp damage. In tests it responded to pokes, burns and cuts. Unlike conventional designs that use separate sensors for each stimulus, this single “multi-modal” material simplifies the hardware while providing rich tactile data. The findings, published in Science Robotics, suggest it could be used on humanoid robots or prosthetic limbs to give them a more human-like touch.

Multi-Modal Touch and Heat Sensing

According to the paper, unlike typical robotic skins, which require multiple specialized sensors, the new gel acts as a single multi-modal sensor. Its uniform conductive layer responds differently to a light touch, a temperature change or even a scratch by altering tiny electrical pathways. This design makes the skin simpler and more robust: researchers note it’s easier to fabricate and far less costly than conventional multi-sensor skins. In effect, one stretchy sheet of this material can replace many parts, cutting complexity while maintaining rich sensory feedback.

Testing the Skin and Future Applications

The research team tested the skin by casting the gel into a human-hand shape and outfitting it with electrodes. They put it through a gauntlet of trials: blasting it with a heat gun, pressing it with fingers and a robotic arm, and even slicing it open with a scalpel. Those harsh tests generated over 1.7 million data points from 860,000 tiny conductive channels, which fed into a machine-learning model so the skin could learn to distinguish different types of touch.

UCL’s Dr. Thomas George Thuruthel, a co-author of the study, said the robotic skin isn’t yet as sensitive as human skin but “may be better than anything else out there at the moment.” He noted that the material’s flexibility and ease of manufacture as key advantages. Moreover, the team believes this technology could ultimately help make robots and prosthetic devices with a more lifelike sense of touch.

Continue Reading

Science

AI Model Learns to Predict Human Gait for Smarter, Pre-Trained Exoskeleton Control

Published

on

By

Scientists at Georgia Tech have created an AI technique that pre-trains exoskeleton controllers using existing human motion datasets, removing the need for lengthy lab-based retraining. The system predicts joint behavior and assistance needs, enabling controllers that work as well as hand-tuned versions. This advance accelerates prototype development and could improve…

Continue Reading

Science

Scientists Build One of the Most Detailed Digital Simulations of the Mouse Cortex Using Japan’s Fugaku Supercomputer

Published

on

By

Researchers from the Allen Institute and Japan’s University of Electro-Communications have built one of the most detailed mouse cortex simulations ever created. Using Japan’s Fugaku supercomputer, the team modeled around 10 million neurons and 26 billion synapses, recreating realistic structure and activity. The virtual cortex offers a new platform for studying br…

Continue Reading

Science

UC San Diego Engineers Create Wearable Patch That Controls Robots Even in Chaotic Motion

Published

on

By

UC San Diego engineers have developed a soft, AI-enabled wearable patch that can interpret gestures with high accuracy even during vigorous or chaotic movement. The armband uses stretchable sensors, a custom deep-learning model, and on-chip processing to clean motion signals in real time. This breakthrough could enable intuitive robot control for rehabilitation, indus…

Continue Reading

Trending