Optical flow is crucial for robotic visual perception, yet current methods primarily operate in a 2D format, capturing movement velocities only in horizontal and vertical dimensions. This limitation results in incomplete motion cues, such as missing regions of interest or detailed motion analysis of different regions, leading to delays in processing high-volume visual data in real-world settings. Here, we report a 3D neuromorphic optical flow method that leverages the time-domain processing capability of memristors to embed external motion features directly into hardware, thereby completing motion cues and dramatically accelerating the computation of movement velocities and subsequent task-specific algorithms. In our demonstration, this approach reduces visual data processing time by an average of 0.3 seconds while maintaining or improving the accuracy of motion prediction, object tracking, and object segmentation. Interframe visual processing is achieved for the first time in UAV scenarios. Furthermore, the neuromorphic optical flow algorithm's flexibility allows seamless integration with existing algorithms, ensuring broad applicability. These advancements open unprecedented avenues for robotic perception, without the trade-off between accuracy and efficiency.

Constructing the new generation information processing system by mimicking biological nervous system is a feasible way for implement of high-efficient intelligent sensing device and bionic robot. However, most biological nervous system, especially the tactile system, have various powerful functions. This is a big challenge for bionic system design. Here we report a universal fully flexible neuromorphic tactile perception system with strong compatibility and a multithreshold signal processing strategy. Like nervous system, signal in our system is transmitted as pulses and processed as threshold information. For feasibility verification, recognition of three different type pressure signals (continuous changing signal, Morse code signal and symbol pattern) is tested respectively. Our system can output trend of these signals accurately and have a high accuracy in the recognition of symbol pattern and Morse code. Comparing to conventional system, consumption of our system significantly decreases in a same recognition task. Meanwhile, we give the detail introduction and demonstration of our system universality.

University of Texas researchers have developed new biocompatible transistors that mimic brain synapses, an advancement that could help scientists rebuild neural pathways or create brain implants. Though the transistors are not ready for use in humans, the team hopes to use them to create brainlike computers that can work alongside the human brain, said Jean Anne Incorvia, an assistant professor of electrical and computer engineering at UT. "There's a big goal in our field of building brain-inspired computers," Incorvia said. "We can imagine that it could seamlessly work alongside a human brain so the human brain is doing processing, and then at some point, it's connected to these (synaptic transistors), which then start doing neuromorphic computer processing with it. So we have this brain-machine combination for doing tasks." The transistors transfer signals in the same way synapses transfer impulses between neurons, co-author Dmitry Kireev said.

Science fiction has just taken one step closer to reality, as scientists have managed to create a living'sweaty' skin for humanoid robots. The material, developed by scientists at the University of Tokyo, not only has a skin-like texture but can also repel water and'heal' itself with a collagen plaster. The method for its creation was published today in journal Matter, and involves dipping a robot finger into a solution of collagen and human dermal fibroblasts - the two main components that make up the connective tissue in human skin. Lead author Shoji Takeuchi said: 'The finger looks slightly "sweaty" straight out of the culture medium. 'Since the finger is driven by an electric motor, it is also interesting to hear the clicking sounds of the motor in harmony with a finger that looks just like a real one.

Oral-B's toothbrush uses AI to grade your teeth brushing habits Your teeth might not be the first thing you think about when it comes to a beauty routine. But you, like most of us, are probably in constant pursuit of a healthy and pearly white smile. Enter: the Oral-B iO Series 9 toothbrush, complete with AI technology. According To The Latest AI Research From Graz University, Intel's Neuromorphic Chips Are UpTo 16 Times More Energy Efficient For Deep Learning Due to their high power consumption, new AI methods that utilize DNNs pose a significant barrier to broader deployment, particularly in edge devices. The use of spike-based neuromorphic electronics is one potential solution to this issue.

It may sound a little unsettling and perhaps more akin to a dystopian sci-fi thriller. But robots could soon feel pain thanks to the development of a new electronic skin which can mimic uncomfortable sensations. The scientists behind the invention say a mechanical hand fitted with the smart skin showed a remarkable ability to learn to react to external stimuli such as a jab in the palm. It uses a new type of processing system based on'synaptic transistors, which mimics the brain's neural pathways in order to learn' to feel pain. Experts have been working for decades to build artificial skin with touch sensitivity, with one widely-explored method featuring an array of contact sensors across an electronic skin's surface to allow it detect when it comes into contact with an object.

The work, reported May 31 in Science, is a step toward creating artificial skin for prosthetic limbs, to restore sensation to amputees and, perhaps, one day give robots some type of reflex capability. "We take skin for granted but it's a complex sensing, signaling and decision-making system," said Zhenan Bao, a professor of chemical engineering and one of the senior authors. "This artificial sensory nerve system is a step toward making skin-like sensory neural networks for all sorts of applications." This milestone is part of Bao's quest to mimic how skin can stretch, repair itself and, most remarkably, act like a smart sensory network that knows not only how to transmit pleasant sensations to the brain, but also when to order the muscles to react reflexively to make prompt decisions. The new Science paper describes how the researchers constructed an artificial sensory nerve circuit that could be embedded in a future skin-like covering for neuro-prosthetic devices and soft robotics.