Articles tagged with Robot Navigation
Scientists at Max Planck Institute for Intelligent Systems developed a novel method for deploying multiple magnetic miniature robots to navigate through complex networks resembling blood vessels. The system allows for simultaneous treatment of multiple locations, saving critical time and enabling localized care.
Scientists at Princeton University develop a system of two robots connected by flexible tether, enabling them to solve complex problems like maze navigation and object gathering. The innovative approach harnesses physical characteristics rather than digital calculation to achieve remarkable abilities.
Researchers developed grain-sized soft robots that can transport up to four different drugs, release them in reprogrammable orders and doses, and navigate complex environments inside the human body. The robots' precision functions have the potential to significantly improve therapeutic outcomes while minimizing side effects.
Researchers at GIST developed a cat's eye-inspired vision system that filters out unnecessary light and improves visibility in low-light conditions. The system promises to elevate the precision of drones, security robots, and self-driving vehicles, enabling them to navigate intricate environments with unparalleled accuracy.
Researchers have developed an octopus-inspired adhesive that can quickly grab and controllably release challenging underwater objects. The adhesive achieves high attachment strength on various surfaces, including rough and curved ones, within a fraction of a second.
Researchers developed a light-driven, toroidal micro-robot that can navigate complex environments like medicine and environmental monitoring. The innovation uses liquid crystalline elastomer to overcome viscous forces and enables autonomous movement in low Reynolds number regimes.
Automated systems with machine learning capabilities improve diagnostic accuracy and workflow efficiency in laboratory medicine. However, ensuring data security, preventing biases in ML models, and maintaining transparency are key concerns.
Researchers at the University of South Australia have developed an AI sensor that can accurately measure the orientation of the Milky Way in low light, using a technique inspired by the dung beetle. This system could improve navigation for drones and satellites in difficult lighting conditions.
Researchers have developed a complex algorithm to choreograph the movement of two robotic arms, ensuring a clear space between them and maintaining a consistent magnetic field. This innovative system uses two robotic arms to steer magnetic medical devices, such as vine robots, with precise control and accuracy.
Researchers at TU Delft developed an insect-inspired navigation strategy for tiny, lightweight robots, allowing them to return home after long trajectories while requiring minimal computation and memory. The strategy combines visual breadcrumbs and step counting to enable autonomous navigation in cluttered environments.
UCF researchers George Atia and Yue Wang received a $1.2 million DARPA grant to develop AI-based technologies that can help autonomous systems adapt to unknown variables and overcome simulation-to-real gap issues.
A new surgical procedure reconnects muscles in the residual limb, allowing patients to receive proprioceptive feedback about their prosthetic limb's position. Seven patients who underwent this surgery were able to walk faster, avoid obstacles, and climb stairs more naturally than those with traditional amputations.
The University of Maryland team created a camera mechanism that mimics the involuntary movements of the human eye, resulting in sharper and more accurate images. The Artificial Microsaccade-Enhanced Event Camera (AMI-EV) has implications for robotics, national defense, and industries relying on accurate image capture.
Researchers from MIT and the MIT-IBM Watson AI Lab devised a navigation method that converts visual representations into pieces of language, which are then fed into one large language model. The approach utilizes purely language-based representations, generating synthetic training data to overcome challenges in visual data availability.
Researchers developed a technique called Multi-View Attentive Contextualization (MvACon) to improve AI's ability to map 3D spaces using 2D images from multiple cameras. MvACon significantly improved the performance of vision transformers in locating objects and detecting speed and orientation.
Researchers developed a novel methodology utilizing digital twins to establish the usefulness of built environment design guidelines for robots. Digital twins allow for real-time monitoring, hazard identification, and training a robot's algorithm before deployment.
A novel approach to training AI systems uses information about spatial position to identify objects and navigate surroundings, inspired by children's visual development. The method improves contrastive learning models' effectiveness by incorporating simulated spatial context information, outperforming base models in various tasks.
Researchers at Princeton University and North Carolina State University have combined ancient paperfolding and modern materials science to create a soft robot that can bend and twist through mazes with ease. The new design allows the flexible robot to crawl forward and reverse, pick up cargo and assemble into longer formations.
An interdisciplinary team of scientists and engineers compared various aspects of running robots with their equivalents in animals, finding that biological components performed poorly compared to fabricated parts. However, animals excel in integrating and controlling these components.
The WVU Research Experience for Undergraduates program aims to solve real-world problems in Appalachia using mobile robotics. Students will conduct independent research in areas like drone navigation and swarming behaviors, focusing on enabling change with robotics tools.
By replicating nature's swarm behavior, researchers have created 'smart swarms' of microscopic robots that can adapt to changing environments, leading to improved task performance. This breakthrough enables potential applications in autonomous drone fleets, efficient drug delivery, and cleaning contaminated water.
A team at the German Cancer Research Center has developed a new method for precise localization of miniature robots and surgical instruments, enabling real-time tracking and control. This breakthrough could advance many medical procedures, including nanorobots for drug transport, tissue measurements, and surgical procedures.
Researchers at University of Missouri are developing software that allows drones to fly independently, perceiving and interacting with their environment while achieving specific goals. This technology has the potential to assist in mapping and monitoring applications, such as 3D or 4D advanced imagery for disaster response.
Researchers have developed a method to decode mouse neural activity, enabling accurate determination of location and direction within an open environment. This breakthrough could inform the design of intelligent machines that navigate autonomously without GPS or satellite guidance.
Researchers discovered how insects navigate using limited brain power by simplifying complex problems through their behavior, a strategy that can be applied to robots and computers. A model of insect neuronal activity showed the robot successfully navigated in various environments, leading to potential improvements in energy efficiency.
A recent study published in The Journal of Bone & Joint Surgery suggests that robotic-assisted surgery and surgical navigation techniques do not significantly increase the risk of periprosthetic joint infection (PJI) after total hip arthroplasty (THA). The researchers analyzed data from nearly 13,000 patients undergoing THA between 201...
Researchers have developed twisted ringbots that can roll forward, spin like a record, and follow an orbital path around a central point. These devices can navigate and map unknown environments without human or computer control.
Korea Maritime & Ocean University researchers have developed a new method for assessing the path-following performance of autonomous ships in adverse weather conditions. The computational fluid dynamics model can provide more accurate predictions of path-following performance and enhance safety in autonomous marine navigation.
A NSF-funded project, MABLE, is developing a digital app using crowdsensing, AI, and robotics to empower individuals with responsive maps and turn-by-turn instructions. The app aims to improve accessibility and navigation for persons with visual or mobility impairments, such as those with low vision and wheelchair users.
The new system enables infrared non-line-of-sight imaging, improving safety and efficiency for unmanned vehicles and robotic vision applications. Spatial resolution of less than 2 cm achieved at both 1560 and 1997 nm wavelengths.
A team of engineers at the University of Pittsburgh has created a new robot that can navigate complex environments using bio-inspired neural networks. The robots will be able to avoid obstacles and learn from their experiences, enabling autonomous navigation for various applications such as commercial transport and disaster response.
Researchers have successfully developed a robot that can autonomously navigate through living lung tissue, avoiding vital structures such as airways and blood vessels. This innovation enables surgeons to reach previously inaccessible small tumors, improving treatment outcomes for patients with lung cancer.
Researchers at Cornell University have created an insect-scale quadrupedal robot powered by combustion that can outrace, outlift, and outflex its electric-driven counterparts. The robot's actuators produce 9.5 newtons of force and operate at frequencies greater than 100 hertz.
Researchers at North Carolina State University have created a soft robot that can navigate simple mazes without human or computer guidance. The new robot has an asymmetrical design, allowing it to turn and move in arcs, enabling it to navigate complex and dynamic environments.
Hang aims to develop general-purpose robots that can handle complex physical interactions without requiring perfect input from sensors or extensive instructions. His project seeks to improve robotic manipulation tasks by reducing assumptions about how the robot acts in real-world conditions.
A team of scientists has developed a novel underwater geolocation technique inspired by migratory animals' navigation methods. They trained a deep neural network to predict geolocation from underwater angle of polarization images collected with an omnidirectional lens, achieving superior accuracy in low-visibility waters and at night.
Researchers at Brown University have developed a krill-inspired robot called Pleobot, which emulates the swimming method of krill to navigate complex marine environments. The platform has the potential to enable scientists to understand how to engineer better robots for ocean navigation and exploration.
Scientists at KTH Royal Institute of Technology created the smallest glass structure by 3D printing with sub-micrometer resolution. The new method eliminates thermal treatment requirements, enabling customized applications in medical machinery, robotics, and telecommunications.
A new study deployed unmanned ground vehicle systems to monitor and eradicate Aedes mosquitos in Taiwanese sewers. The system detected 20.7% of inspected sewers with mosquito traces, leading to a significant reduction in adult mosquito density after intervention.
The HKU team's PULSAR boasts full onboard perception, mapping, and control capabilities in indoor and outdoor environments without external instruments. It can detect static and dynamic obstacles, track complex trajectories, and navigate autonomously even in complete darkness.
Researchers at the University of Washington have developed a multifunctional interface between photonic integrated circuits and free space, allowing for simultaneous manipulation of multiple light beams. The device operates with high accuracy and reliability, enabling applications in quantum computing, sensing, imaging, energy, and more.
HBP researchers develop a robotic platform capable of learning as humans do while navigating around a space. The simulated hippocampus alters its own synaptic connections to remember paths, a marked improvement over current methods relying on deep learning.
The CHEST journal April issue features cutting-edge research on asthma, chronic obstructive pulmonary disease (COPD), and sarcoidosis. Key findings include the potential of efzofitimod as a treatment for managing sarcoidosis. The journal also showcases innovative approaches to clinical practice and education in chest medicine.
Researchers developed a hybrid micro-robot that can navigate in physiological environments and capture targeted damaged cells. The micro-robot uses electric and magnetic mechanisms to identify and transport single cells for further study.
Researchers have developed a robotic system called AngleNet that measures leaf angles on corn plants, providing plant breeders with accurate data more quickly. The technology uses stereo vision and deep convolutional neural networks to capture images of leaves at different heights, enabling 3D modeling and precise measurements.
Researchers have created twin-bioengine yeast micro/nanorobots that can autonomously navigate to inflamed sites in the gut, providing precise delivery of therapeutics via enzyme-macrophage switching. The robots effectively penetrate intestinal mucus barriers and increase drug accumulation at diseased sites.
The NERVE Center has developed test methods and metrics for various robots, identifying limitations to improve systems. The center's success grew its research capabilities through partnerships with NIST and the U.S. Army.
Researchers developed a new non-mechanical 3D lidar system that combines scanning and flash illumination using a chip-based light source, enabling safe navigation in dynamic environments. The system can measure the distance of poorly reflective objects and track their motion, making autonomous driving safer.
The iCPH platform combines physical and cyber elements to capture human motions, using musculoskeletal analysis and machine learning. It generates contact motion networks for humanoid robots and simulates human behaviors, enabling smooth interactions with humans.
Researchers at Incheon National University have developed an IoT-enabled, real-time object detection system for autonomous vehicles. The YOLOv3-based model achieved high accuracy (>96%) in detecting 2D and 3D objects, outperforming other state-of-the-art detection models.
University of Missouri engineers are working on a collaborative human-robot order picking system to speed up the online delivery process. The proposed model aims to optimize key decisions in warehouse operations, allowing robots to navigate efficiently and collaborate with humans to increase efficiency.
Researchers have developed a new miniature robot called Joey that can explore real pipe networks completely on its own, weighing just 70g. The robots are small enough to fit in the palm of your hand and are equipped with energy-efficient sensors to navigate through narrow sections and obstacles.
Researchers at NC State University have developed a ring-shaped soft robot capable of crawling across surfaces when exposed to elevated temperatures or infrared light. The 'ringbots' are made of liquid crystal elastomers in the shape of looped ribbon, resembling a bracelet, and can pull a small payload across various environments.
Researchers develop a modular structure design method for a deployable space robot called Cubot to facilitate on-orbit missions. The system can perform tasks such as space debris removal and maintenance with reduced risk and increased efficiency.
Researchers at WVU are developing software for robots to learn and adapt in real-time, inspired by the neural networks of electric fish. The goal is to enable robots to navigate different terrains autonomously without human supervision.
Researchers at Carnegie Mellon University have developed a new approach for conducting automated science in space by balancing risk and scientific value. The approach uses a model that estimates science value and risk, allowing rovers to chart their own course while protecting against high-risk missions.
The platform enhances neurosurgical procedures by delivering precise treatment and diagnosis in deep brain tissue. Researchers successfully implanted the catheter in live sheep without damage or infection, paving the way for potential human trials within four years.
Researchers develop autonomous navigation strategies for microswimmers, allowing them to navigate optimally in complex environments. These strategies utilize external stimuli, such as light, to guide the microswimmers and improve their performance.
A team from the University of California San Diego has developed a new system of algorithms that enables four-legged robots to walk and run on challenging terrain while avoiding obstacles. The system combines vision with proprioception, allowing the robot to move efficiently and smoothly in various environments.
A new study takes inspiration from the 'waggle dance' of honeybees to devise a way for robots to communicate effectively in situations with unreliable network communications. Researchers designed a visual communication system using on-board cameras, allowing robots to interpret gestures and convey complex information.