Articles tagged with Robot Control
A new soft gripper designed by WVU researcher Anand Mishra can accurately gauge the size, curvature, color, and ripeness of fruits like strawberries and avocados. The gripper's quick inspections and harvesting capabilities can reduce spoilage and lower supply chain costs.
Researchers propose embedding AI foundation models into control software to enable robot swarms to achieve new levels of autonomy and adaptability. This enables robots to switch between tasks in real-time and interact more naturally with humans.
Researchers at Texas A&M University are designing how humans will build and survive on the moon, focusing on sustainable construction using lunar regolith. The institution's efforts aim to reduce costs associated with shipping materials to the moon, making it possible to produce rocket propellant locally.
A robotic hand developed at USC can hear a melody once and play it back after just two minutes of self-taught practice on a keyboard. The system, called the Musician Hand, mimics the way the brain and body coordinate fine motor skills through trial and error, offering a new model for machines — and medicine — to approach complex moveme...
Researchers at Duke University introduce Argus, a 20-eyed robot with no front or back, demonstrating dynamic symmetry and improving performance across various measures. The design surpasses the theoretical maximum of 0.6, enabling robustness, energy efficiency, and resilience to damage.
The NTU Singapore team developed a tiny seed-sized robot that can perform five surgical functions wirelessly, including cutting and releasing drugs. The robot is controlled by weak magnetic fields and takes under a second to switch between functions. It has the potential to make surgeries more precise and safer.
Experts warn that AI-enhanced surgical robotics could enable true personalized surgery and enhance surgical team performance. However, regulatory reforms are needed to address risks from adaptive systems and ensure patient benefits.
Researchers emphasize the need for more thorough frameworks to ensure AI-enabled robots embody human values. The field should focus on three complementary lines of defense: rules that shape robot decisions, checks that monitor behavior, and safety reasoning.
Researchers at Osaka Metropolitan University developed a new AI-powered snake-like robot that optimizes its movement using deep reinforcement learning. The robot's 'rolling motion' achieves twice the travel speed per unit of power consumption compared to traditional slithering motion, making it more efficient on flat surfaces.
Researchers develop Kinematic Intelligence framework to transfer skills between robots with different mechanical structures, enabling safe and predictable behavior. The approach reduces time and expertise needed to deploy robots in real-world settings.
The study, led by Lucy Liu and L. Mahadevan, shows that adding the right amount of noise to individual robot movements can ease gridlock and improve efficiency in crowded environments. The researchers used computer simulations and experiments with small robots to test their ideas.
Soft robots could work as medical implants, deliver drugs inside the body, and explore dangerous environments. The researchers designed a reconfigurable robot that can move repeatedly without degradation, using targeted heating to control motion and embedded temperature sensors for closed-loop control.
Researchers propose a foundational framework to help multi-agent, connected systems decide what information they can trust before acting. The 'cy-trust' concept assigns a numerical trust value between 0 and 1 to data from other agents based on sensing, context, network behavior, and past experience.
IITGN researchers develop a novel control framework for flexible continuum robots, called virtual actuation space (VAS), to improve their precision and scalability. VAS reduces the complexity of controlling multi-section robots by using just two parameters: direction and magnitude.
Researchers at MIT have developed an ultrasound wristband that precisely tracks hand movements, allowing users to control a robotic hand or manipulate virtual objects. The device produces high-quality images of the wrist's muscles and tendons, which are then translated into specific hand positions, enabling precise movement control.
The Center for Scalable and Intelligent Automation in Poultry Processing will hold its first field day on April 9 to share research on developing new robotic technologies. Researchers will demonstrate tools for deboning, detecting foreign materials and pathogens, as well as using virtual reality to operate equipment remotely.
Researchers developed magnetically controlled microrobots made from diatoms to target glioblastoma lesions with photodynamic therapy. The microrobots achieved a significant cytotoxic effect on primary glioblastoma cells and demonstrated good biocompatibility.
Researchers demonstrated a breakthrough in microrobotics: swarms of magnetic microrobots can manipulate objects without physical contact by harnessing fluid-generated torque. The microrobots act as motors to move millimeter-sized passive objects, opening new pathways for precision manufacturing and biomedical applications.
A hierarchical 3D LiDAR localization method improves robot positioning in large outdoor spaces even after seasonal changes. The method integrates deep learning techniques to extract discriminative local features from 3D point clouds, making it robust to environmental variability.
Researchers found that participants initially overestimated the awkwardness of their gait but improved as they practiced using the prosthetic device. Despite significant performance gains, participants remained inaccurate in assessing their own body movement, focusing on torso position rather than prosthetic behavior.
Researchers at the University of Pennsylvania have developed HoloRadar, a system that enables robots to reconstruct hidden 3D spaces beyond their line of sight using radio waves processed by AI. This capability can improve safety and performance in driverless cars and cluttered indoor settings.
Researchers at UC3M develop a new methodology for autonomous arm movement using observational learning and intercommunication between limbs. The ADAM robot can perform daily tasks such as setting and clearing the table, ironing, or tidying up the kitchen with fluid efficiency and natural movement.
Researchers developed a new AI control system that allows soft robots to learn a broad set of motions once and adapt instantly to changing conditions without retraining. The system combines structural learning with real-time adaptiveness, making it suitable for diverse tasks and environments.
A new fabrication method, optofluidic assembly, has been developed to create tiny 3D objects from a variety of materials, including metals, semiconductors and polymers. The technique uses light-driven flow to guide the assembly of micro- or nanoparticles within a confined space.
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.
A team of researchers at EPFL developed a robotic hand that can detach from its arm and 'crawl' to grasp multiple objects, overcoming human asymmetry and limitations. The device can perform 'loco manipulation' with seamless autonomy and has potential applications in industrial, service, and exploratory robotics.
Scientists created biologically realistic artificial cilia using hydrogel, enabling precise control over their motion. The tiny structures can be powered by low-voltage electrical signals and have shown remarkable durability and versatility.
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 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.
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.
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 at the University of Cincinnati developed a flapping wing drone that can hover like a moth around a light source using an extremum-seeking feedback system. The drone makes fine adjustments to maintain stability and distance, without relying on AI or complex calculations.
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.
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.
Frasky, developed by IIT, combines robotics and AI to address environmental sustainability and labor shortages in agriculture. The robot can navigate autonomously, map its surroundings, and apply selective treatments to grape clusters with precision.
Researchers created a new approach that integrates visual and tactile information to manipulate robotic arms, outperforming conventional vision-based methods. This breakthrough represents a significant advancement in multimodal physical AI.
Robotics experts disagree with claims that humanoid robots will surpass human capabilities in surgery, factory work, and serving as personal butlers. The main limitation is dexterity, making tasks like picking up objects difficult for current robot technology.
A team of researchers has developed a robot with self-morphing, wing-like feet that mimic the agile movements of water striders. The insect-scale robot enhances surface maneuverability and can execute sharp turns in just 50 milliseconds, rivaling the rapid aerial maneuvers of flying flies.
A wearable robot has been upgraded to provide personalized assistance to ALS and stroke patients. The device uses machine learning and a physics-based model to adapt to an individual user's movements, offering more nuanced help with daily tasks.
A new robotic slip-prevention method has been developed to improve robots' grip and handling of fragile or slippery objects. This bio-inspired approach allows robots to predict when an object might slip and adapt their movements in real-time, outperforming traditional strategies.
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.
The study reviews recent advances in heterogeneous aquatic robot systems, integrating robots to perform coordinated tasks in complex marine environments. Key findings include the development status of communication, sensing, navigation, control, decision-making, and energy management technologies.
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.
The Association for Computing Machinery has recognized five individuals with awards for their impactful service to the computing field. Manish Parashar received the ACM Distinguished Service Award for his leadership in furthering the transformative impact of computer science on science and engineering.
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.
Researchers developed novel haptic devices to enable precise robot control with tactile feedback, reducing collisions and improving user proficiency. The devices integrate digital twin technology and augmented reality for enhanced immersion.
SWORD accelerates robotics development by reducing manual coding required for complex applications, integrating CAD with open-source ROS tools to streamline automation. The software models, plans, and executes automation in a user-friendly environment.
A team of Brown University researchers has developed an artificial intelligence model called MotionGlot that can generate movement in robots and animated figures. The model enables users to type an action and generates accurate representations of that motion, translating across different robot and figure types.
Researchers at MIT created a table tennis bot that can return shots with high-speed precision, achieving a hit rate of 88% in tests. The technology could be adapted to improve the speed and responsiveness of humanoid robots for search-and-rescue operations.
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.
A new robotic system uses cues in a scene to determine a human's objective and quickly identify relevant objects, enabling intuitive assistance in household, workplace, and warehouse settings. The approach achieved 90% accuracy in predicting human objectives and 96% accuracy in identifying relevant objects.
A new brain-like computer uses analog computing to process and store information in the same location as biological neurons, reducing power consumption by 0.25%. The device, called a memristor network, is more efficient than conventional transistor-based computers and has implications for autonomous vehicles and drones.
A new coffee-making robot, developed by the University of Edinburgh, demonstrates cutting-edge AI and motor skills that enable it to adapt to challenging kitchen environments. The robot can interact with objects and people seamlessly, solving complex problems like accessing drawers and measuring ingredients.
The Harvard robot uses latch-mediated spring actuation to jump high and cover long distances relative to its size. It combines walking and jumping modes for effective navigation in natural environments.
A team of researchers has created a robotic material-like collective that can change shape and stiffness in response to internal signals. The robots, composed of disk-shaped autonomous units, use light sensors, magnets, and force fluctuations to achieve this behavior, reducing power consumption compared to traditional robotic systems.
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 developed a platform to help AI learn complex tasks through nuance and real-time instruction, achieving up to a 30% increase in success rates. The GUIDE framework allows humans to provide ongoing, nuanced feedback, fostering incremental improvements and deeper understanding.