Articles tagged with Autonomous Robots
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The COMET project AutoForst aims to increase safety, alleviate labor shortages, and improve forest logistics with digital and automated systems. Researchers will develop sensor and camera systems to recognize critical situations during loading and automate transport 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.
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.
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.
A team of researchers at the University of Waterloo developed a framework that uses mathematical tools and machine learning to rigorously check and verify the safety of AI-driven systems. The framework has been tested on challenging control problems and matched or exceeded traditional approaches.
A new Physical AI technology cuts driving time for robots in logistics centers and smart factories by up to 30%, improving navigation efficiency through social behavior modeling. The tech allows robots to forget unnecessary information, share important details, and achieve more efficient cooperative navigation.
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.
Researchers at Stanford University created an algorithm that efficiently manufactures products with a team of robots, directing them to work alone or in teams and laying out the assembly floor to prevent collisions. The ability to generate assembly plans quickly could provide flexibility in manufacturing, allowing factories to pivot mo...
Researchers at the University of Minnesota developed AI-guided aerial robots to detect, track and analyze wildfire smoke plumes. The technology provides high-resolution data collection across large areas at a lower cost than satellite-based tools, enabling more accurate computer models for air quality predictions.
Vasile's research aims to map and model an agent's capabilities, particularly in motion, manipulation, and perception, to reliably predict their behavior. The goal is to use this understanding to plan effectively for large teams of agents.
Researchers at North Carolina State University unveiled Rainbow, a self-driving laboratory that autonomously discovers high-performance quantum dots. The system combines advanced robotics and AI to conduct up to 1,000 experiments per day, accelerating materials discovery.
Researchers created dynamic metashells that leap into the air on a predetermined schedule without intervention, jumping up to nine times their height. The structures were engineered to store energy and release it at a controlled timing, with scheduled jumps possible from three seconds to 58 hours in advance.
Researchers developed an intelligent autonomous robot capable of automating hospital disinfection processes through dual disinfection system, increasing efficiency and precision. The robot's performance was validated through real-world testing, reducing the risk of infection in hospitals.
Scientists used virtual reality to mimic schooling behavior in zebrafish, discovering a simple and robust control law that enables coordinated motion. This natural algorithm was then applied to swarms of robotic cars, drones, and boats, achieving performance comparable to state-of-the-art autonomous systems.
A soft robot can carry loads through the air along established tracks, navigating angles of up to 80 degrees and carrying loads up to 12 times its weight. The robot uses infrared light to move along the track, repeating a rolling motion that pulls it forward.
Researchers at Osaka Metropolitan University developed an autonomous driving algorithm for robots to navigate raised cultivation beds, utilizing lidar point cloud data. The system enables precise movement and accuracy in both virtual and actual environments, promising to expand tasks beyond harvesting to monitoring and pruning.
A research paper proposes an earthworm-inspired soft robot with a novel wire-winding transmission mechanism, achieving multimodal motion and superior motion efficiency. The robot surpasses other robots of the same type in planar crawling speed by an order of magnitude.
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.
A tiny, soft robot developed by Penn State researchers can navigate through debris and deliver medicine inside the body. The flexible electronics system enables smart sensors to interact with its surroundings, allowing the robot to operate with minimal human intervention.
Researchers at Kumamoto University have developed a new mathematical modeling technique for linear periodically time-varying systems, enhancing the accuracy of control system models. This breakthrough has profound implications for industries relying on complex control systems, such as autonomous vehicles and aerospace applications, imp...
Researchers are developing soft-bodied actuators, shape-adaptive propulsors, and AI-driven control strategies to improve energy efficiency and adaptability in MURs. Future innovations may enable robots to mimic marine organisms with unprecedented fluidity and facilitate swarm robotics for collective exploration.
This groundbreaking research systematically reviewed construction robots' scientific technologies and progress in extreme environments, including hazardous work environments, polluted environments, and harsh natural environments. The study elucidated four key technical performance aspects: mechanism, perception, planning, and control.
State-of-the-art AI models struggle to interpret clock-hand positions and answer questions about dates on calendars, requiring spatial awareness, context, and basic maths. Researchers tested various clock designs with different fonts and styles and found that AI systems got clock-hand positions right less than a quarter of the time.
Researchers develop active metamaterials that can autonomously roll, crawl, and wiggle over unpredictable terrain, including uphill and obstacles. These 'odd' objects achieve motion through unusual interactions between motorized building blocks, demonstrating decentralized and robust locomotion.
Researchers at Yokohama National University have developed a tiny, low-weight robot that can act independently and with ultra-high precision in extreme environments. The Holonomic Beetle 3 (HB-3) integrates piezoelectric actuators with autonomous technology for precise manipulation tasks, addressing industries such as laboratory automa...
Researchers from the University of Washington have developed an assistive feeding arm that can help people with motor impairments feed themselves. The system, dubbed ADA, uses a robotic arm and web app to deliver meals autonomously, with users able to customize its functionality.
A bioinspired robot called GOAT can change shape to alter its physical properties in response to the environment, resulting in a robust and efficient autonomous vehicle. The robot's compliance allows it to navigate diverse environments with minimal sensing equipment, enabling it to find the path of least resistance.
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 at Columbia University developed a way for robots to autonomously model their own 3D shapes using a single camera, enabling them to understand and adapt to their movements. This breakthrough allows robots to overcome damage to their bodies, making them more reliable and resilient for various applications.
Ebru Demir aims to study how groups of AI-driven microswimmers move in biological fluids for potential applications in drug delivery, fertility treatments, and other medical fields. Her research combines artificial microswimmers with machine learning to uncover the underlying physics governing their movement.
Researchers created robotic materials that can change shape, support heavy loads, and self-heal by enabling dynamic inter-unit forces and biochemical signaling. The system can be scaled to thousands of units, enabling the development of robust and adaptable robotic materials.
Researchers develop a novel adaptive nonlinear PID controller integrated with radial basis function neural network for enhanced ballbot functionality. The proposed NPID-RBFNN controller demonstrates superior stability and robustness, outperforming traditional PID and NPID controllers.
Researchers at Japan Advanced Institute of Science and Technology developed Leafbot, a soft robot that uses vibration-driven locomotion to traverse uneven surfaces. The robot's compliant structure and simple motion strategy enable it to overcome complex obstacles, making it valuable for applications such as inspection and exploration.
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.
Researchers are developing a software framework for crowd-sourced 3D map generation and visual localization from camera data to improve real-time updates and low-cost visual localization. This technology aims to advance self-driving vehicles and enable fully automated transportation
A new 6D pose dataset has been introduced, providing high-quality RGB and depth images with annotated 6D pose data. This dataset achieves state-of-the-art accuracy rates of 97.05% and 98.09% for robotic grasping and automation applications.
Researchers advise reprogramming and repurposing robots for sustainable use, as current recycling methods are often ineffective. The study aims to challenge the robotics industry to design for a circular economy, addressing challenges such as economic viability and technical capability.
The University of Virginia's AI-powered vision system, mimicking praying mantis eyes, has been selected as the best paper of 2024 by Science Robotics. The innovative system enables machines to track objects in 3D space, addressing limitations in current visual data processing.
Researchers from Singapore, Japan and US developed an advanced swarm navigation algorithm for cyborg insects that prevents them from getting stuck in challenging terrain. The new algorithm represents a significant advance in swarm robotics and could pave the way for applications in disaster relief and search-and-rescue missions.
Scientists have developed swarms of tiny magnetic robots that can lift and transport heavy objects, thanks to their unique assembly configuration and rotating magnetic field. The microrobots can even guide small organisms through complex motions.
Researchers discover that modifying BallBot's body mass and ball size can significantly improve its balancing abilities, enabling more stable and reliable robots. The study introduces a Linear Quadratic Regulator (LQR) controller to fine-tune the robot's movements, allowing for improved balance and stability in dynamic environments.
Researchers created a measurement scale to assess robot human likeness, revealing four key qualities: appearance, emotional capacity, social intelligence, and self-understanding. To seem lifelike, robots must exhibit these traits, with self-understanding being the most challenging aspect to simulate.
The EPFL researchers built a drone with birdlike legs that can walk, hop, and jump into flight, greatly expanding the potential environments for unmanned aerial vehicles. The design allows it to take off autonomously in previously inaccessible environments.
The LabEmbryoCam is a robotic instrument that autonomously monitors embryonic development in aquatic species, providing insights into how environmental conditions impact early life stages. The open-source instrument enables scientists to track key features such as heart rate and growth in large numbers of embryos simultaneously.
The Center for Marine Autonomy and Robotics develops advanced underwater robots and autonomy algorithms, enabling intelligent operation without human oversight. The research team has received $7.4 million in grants to continue their mission, advancing unconventional marine platforms and enhancing AUV capabilities.
A team of Caltech researchers has developed an algorithm called Spectral Expansion Tree Search (SETS) that enables autonomous robots to determine the best movements to make as they navigate the real world. SETS uses control theory and linear algebra to find natural motions that use a robotic platform's capabilities to its fullest extent.
Scientists at the University of Sydney create programmable nanostructures using DNA origami, enabling rapid prototyping of diverse configurations. These custom-designed nanostructures have potential applications in targeted drug delivery, responsive materials, and energy-efficient optical signal processing.
The In-Space Physical AI Workshop, held at Rice University's Ion District, brought together top scientists and experts to explore AI applications in space. Key findings included the potential of AI to streamline spacecraft navigation and crew health management.
A new study suggests that smart robots can predict waves in real-time, enabling them to work stably in turbulent seas. This technology could reduce the cost of generating renewable energy by up to 50%, making it more competitive with fossil fuels.
The Naval Research Laboratory (NRL) has successfully developed a robotic suite capable of servicing satellites in orbit, enabling resilience for the US space infrastructure. The Robotic Servicing of Geosynchronous Satellites Integrated Robotic Payload (IRP) will enable satellite upgrades and repairs, reducing complexity and cost.
PanoRadar leverages radio waves and AI to enable robots to navigate challenging environments like smoke-filled buildings or foggy roads with high resolution. The system combines measurements from all rotation angles to enhance imaging resolution, creating a dense array of virtual measurement points.
Researchers from Johns Hopkins University have developed a robot that can perform surgical procedures with the same skill as human doctors, eliminating the need to program robots with individual moves required during surgery. The 'imagination' model uses imitation learning to train the da Vinci Surgical System robot, enabling it to pre...
Researchers at the University of Liverpool developed AI-driven mobile robots that can perform exploratory chemistry research tasks faster and more efficiently than humans. The robots use AI logic to make decisions, processing analytical datasets in real-time to determine the next steps in chemical synthesis.
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 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 from UNC-Chapel Hill propose that robotic automation and AI can transform science labs, speeding up experiments and unlocking breakthroughs in health, energy and electronics. Automation reduces human fatigue, increases precision and improves safety, enabling scientists to focus on higher-level research questions.
Researchers developed MobiPrint, a mobile 3D printer that can measure and print objects onto the floor. The system can add accessibility features, such as tactile markers, and create custom objects like art pieces.
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.