Articles tagged with Robotics
Researchers have developed a strong, defect-free composite material that can phase-shift under stress to dissipate energy. The material, created using additive friction stir deposition, has potential applications in defense, infrastructure, aerospace, and sporting equipment.
Researchers used robotics and 'click' chemistry to synthesize over 700 metal complexes in a week, identifying six potential new lead compounds. An iridium-based antibiotic candidate showed high effectiveness against bacteria while being non-toxic to human cells.
A team of researchers developed a multi-material, multi-module microrobot that can grab, carry and release microscopic objects. The microrobot features two parts: one reacts to pH changes to grip an object, while the other responds to magnetic fields for movement.
A new AI framework uncovers simple, understandable rules governing complex dynamics in nature and technology. The AI generates equations that accurately describe complex systems, revealing hidden variables that govern their behavior. This approach offers scientists a new way to leverage AI for understanding complex systems.
Researchers propose integrating processing capability within memory units to reduce energy consumption and latency in AI applications. Inspired by the brain's efficient processing mechanisms, spiking neural networks (SNNs) can respond to irregular events and store information in the same place.
Researchers propose a novel approach to AI hardware design by integrating neuromorphic systems and compute-in-memory techniques to overcome the limitations of modern computing hardware. This could lead to more efficient data center energy use and enable real-time intelligence in compact, power-constrained systems.
Researchers at Penn and UMich created microscopic swimming machines that can independently sense and respond to their surroundings, operate for months, and cost just a penny each. The robots are powered by light and can be programmed to move in complex patterns, sense local temperatures, and adjust their paths accordingly.
Developed by U-M and Penn, the robots can sense and respond to their surroundings, operate for months, and cost just a penny each. They have applications in monitoring cell health and aiding manufacturing.
A Harvard-designed bio-logger captures high-fidelity audio of sperm whale codas, which are later analyzed by machine learning models to uncover structured communication. Recent results show that sperm whales have their own alphabet and use vowels and diphthongs in their language.
Researchers developed a novel bioelectronic material that transforms from a rigid film to a soft, tissue-like interface upon hydration, enabling seamless integration with living tissues. The device, called THIN, has been shown to record biological signals with high fidelity and stability in animal experiments.
The startup aims to bring human integration and industrial usability to its robots, which will operate safely and efficiently in industrial environments. The company's mission is to create a future where humans and robots collaborate daily.
A new robotic design uses vine-like structures to lift and grasp a variety of objects, including humans, with a gentler approach. The robot can snake around obstacles, squeeze through tight spaces, and even secure itself in a closed loop to create a sling.
Rothemund aims to harness phase transitions to improve controllability of soft robots, enabling tasks like grasping and crawling through tight spaces. The project seeks to develop new materials and a model robot arm for three-dimensional motion control.
University of Utah engineers developed an autonomous approach using proximity and pressure sensors, training an artificial neural network on grasping postures. Study participants demonstrated improved grip security, precision, and less mental effort when using the AI-enhanced prosthesis.
A breakthrough AI system called OmniPredict can predict human pedestrian behaviors with unprecedented accuracy, revolutionizing self-driving cars and urban mobility. The model combines visual cues with contextual information to anticipate pedestrians' next moves, reducing the risk of accidents and improving traffic safety.
Researchers at Stanford University have successfully used machine-learning-based control to operate a robot on the International Space Station, allowing for faster and more efficient navigation while maintaining safety. The system, which includes a warm start feature, enables robots like Astrobee to move through complex environments wi...
A new model developed by Osaka Metropolitan University Assistant Professor Takuya Fujinaga enables robots to accurately pick tomatoes, with an 81% success rate. The system evaluates the ease of harvesting for each tomato, taking into account factors such as fruit clustering and stem geometry.
The MIT team developed a new AI-based controller that enables the robot to follow gymnastic flight paths, such as executing continuous body flips. The robot's speed and acceleration increased by 450% and 250%, respectively, compared to previous demonstrations, making it comparable to insects in terms of agility.
Collaborative robots require adaptive solutions to handle dynamic environments. A new approach integrates reactive planning and control, enabling seamless interaction with humans and surroundings. The method uses combined learning and optimization to generate feasible motion for mobile manipulators, improving efficiency and performance.
MIT engineers developed artificial tendons made from hydrogel to connect lab-grown muscles with robotic skeletons. The tendons improved the robot's motion and force output by three times, enabling faster and more efficient biohybrid robots.
The UBC robotic platform helps scientists understand how the brain keeps us standing by mimicking delays in sensory feedback. By tweaking forces and adding short delays, the robot reveals that our sense of space and time work from the same playbook.
In a study by SWPS University, researchers found that children interact with polite robots almost always respond politely. Younger children and girls are more likely to anthropomorphise the robot, suggesting social cues in interactions between children and robots are crucial for positive learning outcomes.
Scientists at Seoul National University create an interlaced origami structure that can be folded, rolled up for storage, and deployed with high strength. The design overcomes limitations of traditional corrugated structures, enabling multi-layer folding and smooth unwinding.
Researchers developed soft robots inspired by manta rays, utilizing magnetic fields to move, recharge power supply, and perform tasks autonomously. The magnets stabilize electrochemical reactions in flexible batteries, enhancing performance and efficiency.
Researchers develop soft fiber-like pumps powered by ambient energy to drive the next generation of robots and wearable devices. The innovation enables robots that operate autonomously and wearable devices that provide comfort without cumbersome batteries.
Researchers developed a new robot self-modeling approach using part-based Neural Radiance Fields, eliminating the need for depth sensors and human annotation. The system enables robots to build dynamic 3D models of themselves, accelerating the deployment of autonomous machines in unpredictable environments.
A new survey provides a three-module framework for Embodied AI, addressing perception, decision-making and execution. The goal is to develop general-purpose intelligent agents that can perform complex tasks like cleaning the room.
Researchers developed a 3D lattice iontronic sensor that accurately detects sophisticated tactile interactions by linearizing both electrical responses and mechanical behaviors. The sensor, comprising a hydrogel lattice encapsulated in an origami-inspired framework, enables precise detection under extreme dynamic loading.
Researchers at ETH Zurich developed microrobots that can navigate blood vessels with precision, delivering drugs directly to the target location. The robots use magnetic nanoparticles and advanced navigation systems to avoid obstacles and reach their destination.
The new statistical method adapts to data structure, resisting outliers and providing greater stability on non-Euclidean spaces. This improves the reliability of analysis in areas like medical imaging, computer vision, and machine learning.
The researchers developed a chromatic filtration strategy to narrow the emission spectrum of mechanoluminescent materials, resulting in high spectral resolution and reduced noise. The new technology has significant potential for applications such as wearable sensors and healthcare motion monitoring.
The University of Houston is designing robotic hands with dexterity for industries such as healthcare, agriculture, and manufacturing. The team, part of the NSF Convergence Accelerator program, has received $5 million in funding to develop hybrid polymeric materials that can mechanically retract and perform motions like flexion.
Oxford researchers have developed soft robots that operate without electronics, motors, or computers, using only air pressure to generate complex, rhythmic movements. The robots can automatically synchronize their actions and perform tasks like sorting beads into containers without external control.
Researchers explore Field-assisted Additive Manufacturing for micro/nano device fabrication, enabling targeted motion, cell growth, and flexible electronics. The technology holds promise for industries such as biomedical engineering and microrobotics.
Researchers have developed a new class of artificial muscles that respond to ultrasound, enabling precise movements and wireless control. The technology has vast potential for future medical and technical applications, including drug delivery, cardiac patches, and minimally invasive procedures.
The Omnia bionic leg, developed by the Italian Institute of Technology, won the Cybathlon 2024 leg prosthesis race with its semipowered knee and ankle system. Andrea Modica, a transfemoral amputee and pilot of the device, successfully completed 9 out of 10 tasks in just 2 minutes and 57 seconds.
A team of biomechanical engineers and surgeons has developed a 3D-printing soft robot that can accurately deliver hydrogels to the vocal cord surgical site. The device, which is only 2.7 mm in size, can reconstruct tissues removed during surgery and potentially prevent fibrosis and stiffening of the vocal cords.
Scientists develop molecular strategies for creating soft materials that can sense, move, and evolve in response to their environment. Three key principles of supramolecular robotics enable programmed motility, phase transitions, and prototissue formation.
Scientists have replicated the neural circuitry that allows zebrafish to react to visual stimuli and maintain their position in flowing water. The research, published in Science Robotics, used simulations and robots to study embodiment, or how the body affects perception, in larval zebrafish.
Worcester Polytechnic Institute Professor Nitin Sanket has been awarded a $704,908 NSF grant to develop sound-based navigation systems for small aerial robots. The project aims to enable drones to navigate in environments where cameras and light-based sensors fail.
A team of researchers has developed a tiny, spider-inspired robot that can navigate the digestive system with ease, delivering therapy precisely where it's needed. The soft robot overcomes challenges faced by traditional endoscopes, showcasing its adaptability in traversing complex environments.
Researchers created microscopic DNA 'flowers' that can change shape and behavior in response to their surroundings. These tiny robots, made from special crystals formed by combining DNA and inorganic materials, can perform tasks on their own, from delivering medicine to cleaning up pollution.
The LiteRBS algorithm outperforms classical algorithms like A* and Bidirectional A*, scaling well even in large or dense maps. It achieves fast and memory-efficient pathfinding through an aggressive bidirectional forward search with a reserve-queue fallback strategy.
Researchers develop novel dual-laser method to create adaptive, shape-locking devices. The material integrates a shape-memory polymer skeleton with magnetic microcapsules, allowing for 'writing' and 'bending' of instructions and shapes in situ.
Researchers developed a method to trigger magnetic jamming in materials using wireless magnetic fields, enabling reversible and programmable clumping. This technique allows for the creation of structures that can assemble, stiffen, relax, or break apart under magnetic control.
Researchers at North Carolina State University created a class of robots called metabots that can change shape and adapt to different environments. The devices can execute various actions despite having no motor or being made of a single flat material.
Researchers developed a soft robotic skin that allows vine robots to navigate convoluted paths and fragile environments. The robot is steered by controlling the pressure inside its body and temperature of the actuators.
A team of engineers at Harvard John A. Paulson School of Engineering and Applied Sciences designed a proof-of-concept walking robot using only four moving parts connected by rubber bands and powered by one motor. The robot can find its way through mazes, avoid obstacles, and sort objects by mass without electronic control systems.
A recent study reveals that the response to witnessing robot mistreatment depends on factors such as the robot's humanlike design and the observer's moral identity. Anthropomorphism influences empathy, encouraging customers to treat robots with dignity, while moral identity plays a crucial role in shaping behavioral contagion.
A recent study published in PLOS Biology found that combining non-invasive brain stimulation and robotic rehabilitation can significantly improve motor recovery in a mouse stroke model. The treatment restored parvalbumin interneuron dynamics, leading to better motor function.
Researchers develop autonomous nano-robotic systems that utilize scanning electron microscopy for real-time visual feedback, enabling high-precision manipulation of nano-objects. The integration of machine learning-enhanced vision algorithms and novel actuation techniques facilitates adaptive, perception-driven atomic engineering.
Researchers developed a new control algorithm that enables powered knee prostheses to mimic natural human motion, reducing tripping risks and strain on users' bodies. The study showed significant improvements in activities of daily living, such as sitting, standing, walking, and climbing stairs.
MIT researchers developed a new framework that helps engineers design complex systems explicitly accounting for uncertainty. The framework allows them to model the performance tradeoffs of a device with many interconnected parts, each of which could behave in unpredictable ways. This approach can help engineers develop complex systems ...
A study by Osaka Metropolitan University found that pairs outperformed individuals in a robotic arm-transporting task when roles naturally emerged. Role specialization was key to superior performance, rather than paired interaction. The research has implications for human-robot collaboration and rehabilitation settings.
A groundbreaking soft robot has been engineered to perceive and respond to multiple environmental cues simultaneously. Weighing just 8 milligrams, it can carry a payload 2.5 times its own body weight over complex terrain, showcasing impressive agility and strength.
The SRI model integrates swarm dynamics with dynamic graph neural networks, resolving existing method pitfalls. It demonstrates significant performance improvements over traditional methods, with reduced long-term prediction errors.
A novel detection framework, SORA-DET, is introduced for UAV remote sensing, achieving high accuracy and efficiency while being compact and fast. It outperforms large-scale models with up to 88.1% fewer parameters.
The Leopoldina Annual Assembly focuses on the current developments and potential uses of artificial intelligence in various fields, including medicine, geosciences, and physics. The event features keynote lectures, panel discussions, and an award ceremony to recognize outstanding researchers in AI.
Researchers developed a platform called CRESt that incorporates insights from literature, chemical compositions, and imaging to optimize materials recipes. CRESt uses robotic equipment for high-throughput testing and large multimodal models to further optimize materials recipes.
Researchers at CARS create detailed maps of chemical reactivity, discovering regions of unexpected outcomes and reconstructing intricate reaction networks. This new understanding enables control over the formation of different major products from a set of starting materials.