Articles tagged with Aerial Robots
A team of researchers at TU Delft has developed a tactile drone that uses soft tactile sensors in a human-like hand to detect and grasp branches before landing. The drone's approach is robust and accurate, even in situations where vision alone is unreliable.
Researchers developed a disturbance observer to compensate for external disturbances, allowing the robot to reject disturbances while maintaining stable flight. The approach reduced the X-axis position error by 53.1% and improved overall stability.
Northwestern University engineers created a drone called Phantom Twist that harnesses motion blur to blend into its surroundings. The drone spins up to 25 times per second, making it difficult for humans to see clearly, and can potentially monitor wildlife or inspect infrastructure with less disruption.
A new robot designed by MIT engineers can swim underwater and fly through the air, mimicking the abilities of diving birds. The robot's wing flapping frequency and tail angle were adjusted to enable a smooth transition from swimming to flying.
Researchers from Delft University of Technology developed a new way to predict drone instability using critical slowing down, a phenomenon from ecology and climate science. This approach can help detect system failures in real-time, allowing for adaptive strategies to maintain flight despite damage.
Scientists created a shape-changing flying robot named Floaty that can fly efficiently while staying stable in the air. By adjusting its flaps to control air resistance, Floaty balances itself and recovers from disturbances.
A new open-source trajectory-planning system, MIGHTY, has been developed by researchers at MIT and the University of Pennsylvania. The system enables robots to generate smooth flight paths while reacting to obstacles in real-time, making it suitable for applications such as search-and-rescue, last-mile delivery, and industrial inspection.
A team of scientists has developed a novel navigation strategy inspired by honeybees, allowing small robots to travel far away from home and return successfully. The 'Bee-Nav' system uses a neural network to process panoramic images of the environment, enabling lightweight, safe robots to navigate on their own.
Researchers at Worcester Polytechnic Institute developed a palm-sized aerial robot that uses ultrasound sensors and AI to navigate through fog, smoke, and other difficult conditions. The drone achieved a success rate of 72% to 100% in navigating challenging courses during 180 tests.
A drone equipped with low-cost air quality sensors has revealed unexpectedly high concentrations of particulate matter at around 100 meters above ground level in Delhi. The findings suggest that current model simulations underestimate PM2.5 mass concentrations during morning haze episodes, highlighting the need for better mitigation st...
Researchers have identified a new vulnerability in AI-powered robots, where malicious text on signs or objects can hijack their decision-making. The study, led by UC Santa Cruz professors Alvaro Cardenas and Cihang Xie, presents the first academic exploration of environmental indirect prompt injection attacks against embodied AI systems.
Scientists at TU Delft developed an algorithm allowing multiple autonomous drones to work together to control and transport heavy payloads even in harsh weather. The system enables drones to lift and orient a payload with precision, ideal for reaching infrastructure like offshore wind turbines.
Florida International University researchers have developed a defensive system called SHIELD that can detect and neutralize cyberattacks on drones in real time. The system allows the drone to finish its mission while providing robust recovery mechanisms, making it crucial for securing commercial drone use across industries.
Researchers at IIT have successfully demonstrated the first flight of a humanoid robot, iRonCub3, which can lift off the floor and maintain stability. The robot's AI-powered control system enables it to handle high-speed turbulent airflows, extreme temperatures, and complex dynamics.
Aerial robots are limited to manipulating rigid objects, but Lehigh University researcher David Saldaña aims to expand their capabilities with an adaptive controller and reinforcement learning. His research has potential applications in construction, disaster response, and industrial automation.
The Harvard RoboBee has been equipped with crane fly-inspired legs and an updated controller, allowing it to land safely on various surfaces. The robot's delicate actuators were protected by the improved design, which enabled controlled landing tests on a leaf and rigid surfaces.
Scientists successfully developed a method to precisely control the flight altitude of robo-pigeons using targeted electrical stimulation of the LoC nucleus. The study found that stimulation frequency and cycle can effectively control altitude, while increasing neural fatigue is minimized with proper inter-stimulus interval.
Researchers created a hopping robot that can traverse challenging terrains, carry heavy payloads, and uses less energy than aerial robots. The robot's springy leg and flapping-wing modules enable it to jump over obstacles and adjust its orientation mid-air.
The new robot is shaped like a small propeller and uses an external magnetic field to generate lift and control its flight path. It is less than 1 centimeter in diameter and weighs only 21 milligrams, making it the world's smallest wireless flying robot capable of controlled flight.
Researchers developed a submersible robot that leverages vortices to boost efficiency in autonomous underwater vehicles. By 'surfing' vortex rings, CARL reduces energy consumption by one-fifth compared to traditional methods.
Researchers developed a novel bio-hybrid drone by integrating robotic technology with biological odor sensors from insects, overcoming visual sensor limitations. The drone's enhanced performance enables accurate odor detection and tracking, broadening applications in gas sensing, disaster response, and rescue operations.
MIT researchers have introduced a new system called MiFly that enables drones to self-localize in indoor, dark, and low-visibility environments. The system uses radio frequency waves reflected by a single tag placed in the environment, allowing the drone to estimate its trajectory with high accuracy.
Two EU-funded projects presented digital, robotic, and other technologies for improved road monitoring and maintenance, emphasizing the need for automation, data-driven solutions, and sustainability. High-level participants highlighted the importance of collaboration and regulation in paving the way for smarter infrastructure management.
A team of MIT engineers has developed a training method for multiagent systems that can guarantee their safe operation in crowded environments. The method enables agents to continually map their safety margins, allowing them to scale up to any number of agents while maintaining system safety.
A new reinforcement learning framework, AVATARS, uses diverse sensor streams to track whales and predict their surface locations. The framework aims to minimize missed encounters and improve data collection for Project CETI.
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.
A DNA-collecting drone has been developed to identify species in tree canopies, providing insights into remote habitats. The drone's specialized fabric probe collects environmental DNA from leaves and branches, allowing researchers to identify organisms such as arachnids, insects, and monkeys.
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.
Scientists have unveiled that beetles' hindwings are passively deployed and retracted, leveraging the elytra to deploy and retract while flapping forces unfold the wings. This finding has potential applications in designing new microrobots that can fly in confined spaces.
Scientists have discovered how flies track chemical plumes in still air using a combination of environmental cues and innate behaviors. By remotely controlling neurons on the antennae of flying fruit flies, researchers have uncovered two automatic search strategies: sink-and-circle and cast-and-surge behavior.
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.
Eötvös Loránd University researchers develop first large-scale autonomous drone traffic solution, combining route planning and bio-inspired flocking models to avoid conflicts and manage remaining issues. The system can handle up to 5000 drones in two dimensions with varying speeds and priorities.
Researchers developed artificial maple seeds that can be controlled using light to monitor environmental conditions, such as pH levels and heavy metal concentrations. The technology has potential applications in search-and-rescue, endangered species studies, and infrastructure monitoring.
Researchers at Delft University of Technology use drone racing to test neural-network-based AI control systems planned for next-generation space missions. The goal is to achieve optimal onboard operations by continuously replanning trajectories, reducing resource consumption and boosting mission autonomy.
Researchers present a novel protocol structure for achieving global/semi-global finite-time consensus in multi-agent systems. The protocols use a hyperbolic tangent function to guarantee consensus and provide explicit calculation of settling time, making them practical for real-world applications.
The team aims to create a system that can deliver items without human contact, using cables, knots, and multiple robots. They will focus on scaling up the transport of small objects like a basketball and solar panel.
Researchers at Delft University of Technology developed a drone that flies autonomously using neuromorphic image processing and control based on the workings of animal brains. The drone's deep neural network processes data up to 64 times faster and consumes three times less energy than when running on a GPU.
In Brazil, around 90% of sugarcane area uses natural enemies like microorganisms and biochemicals for pest control. Researchers have registered over 629 biological products, with a steady increase in use year after year.
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.
Researchers at the University of Sydney and Queensland University of Technology have developed a new approach to designing cameras that process and scramble visual information. The approach, known as 'sighted systems,' creates distorted images that can still be used by robots to complete tasks but do not compromise privacy.
The CEC researchers have received funding to transform Eagle Bank Arena into a one-of-a-kind robotics experimentation and competition venue. This unique facility will enable the study of multi-robot systems in adversarial settings, advancing the state-of-the-art in heterogeneous multi-robot technologies.
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.
A team of researchers at Oregon State University has demonstrated that a swarm of over 100 autonomous ground and aerial robots can be supervised by one person. The study used virtual reality interface I3 to enable high-level control, allowing the commander to deploy systems without manually driving each individual vehicle.
Researchers developed a network that combines 3D LiDAR and 2D image data to improve small object detection accuracy. The model outperformed existing methods in various noise conditions, with average precision improvements of up to 7.18%.
A Japanese research team developed a four-meter-long, remotely controllable flying firehose robot called the Dragon Firefighter. It can safely and efficiently extinguish fires by directly approaching flames. The robot will be deployed in real-world firefighting scenarios after approximately 10 more years of development.
The Acer i-Seed is an eco-friendly artificial seed that uses drones to monitor soil temperature. Made from biocompatible and compostable materials, it replicates the aerodynamics of natural Acer seeds and becomes luminescent in response to temperature changes.
A team of engineers from the University of Illinois has developed a long-jumping robot with a lightweight elastomer body and artificial muscle made from coiled nylon fishing line. The robot can jump 60 times its body size in horizontal distance, opening up new possibilities for sensing and exploration applications.
Researchers are working on EdgeRIC: Real-time radio access network intelligent control, aiming to enhance wireless communication and machine learning. The project involves developing intelligent systems that can adapt to changing conditions, prioritizing users and acquiring lower latency for applications.
Researchers at the University of Washington have developed small robotic devices that can change their shape in mid-air using a Miura-ori origami fold, enabling battery-free control over descent. The devices can transition from tumbling to falling states, allowing for precise landings in turbulent wind conditions.
A team of researchers from the University of Zurich and Intel has developed an AI system called Swift that can beat human champions in drone racing. The autonomous drone achieved the fastest lap, winning multiple races against three world-class champions, but human pilots proved more adaptable to changing conditions.
MIT researchers developed a new algorithm that can execute complex maneuvers like loops and rolls for tailsitter aircraft, enabling agile trajectories with fast-changing accelerations. The algorithm uses differential flatness to ensure feasibility and planning in real-time.
A team of researchers from Nanjing University of Aeronautics & Astronautics developed a bionic robot that can complete smooth movement, including landing on a vertical wall, climbing along the wall, and taking off from the wall. The robot uses a flapping/rotor hybrid power layout to mimic insect's control of body posture.
Researchers analyzed 1.8 million aircraft operations and 460,000 sUAS flights to identify 24 near-midair collisions. The study suggests extending runway exclusion zones for drones at high-risk airports to improve safety.
Researchers at Imperial College London developed a heat-resistant drone called FireDrone that can withstand temperatures of up to 200°C for ten minutes. The drone provides crucial first-hand data from danger zones to inform emergency response and help save lives.
Researchers at Arizona State University have designed a drone with an inflatable frame that can absorb impact forces and provide collision resilience. The drone's stiffness is tunable, allowing it to physically interact with its surroundings and accomplish tasks like perching, which involves controlled collisions.
Researchers developed ProTac, a soft robotic link with multimodal perception to improve human-robot interactions. The device incorporates tactile and proximity sensing capabilities, enabling robots to react safely and predictably to physical contact.
Researchers developed a robust multiagent trajectory-planner that enables drones to generate collision-free trajectories even with delayed communications. The system achieved a 100% success rate in simulations and flight experiments, guaranteeing safe group operations.
Researchers at MIT have created a way for tiny robots to recover from severe damage to their wings, enabling them to sustain flight performance. The development uses laser repair methods and optimized artificial muscles that can isolate defects and overcome minor damage, allowing the robot to continue flying effectively.
Assistant Professor Samik Bhattacharya is studying bird wing morphing to engineer stable solutions for unmanned aerial vehicles and micro air vehicles. His research could lead to improved control during airflow disturbances, reducing anxiety for pilots.