Articles tagged with Robot Control
Researchers at Cornell University have developed microrobots that can sense temperature and coordinate to change their environment. The robots use a feedback loop inspired by natural systems to alter physical conditions, such as pumping liquid from hot to cold regions.
Researchers at Harvard and Georgia Tech have developed RLE-Bench, a benchmark that tests AI coding agents' ability to engineer physical robots. The benchmark contains 48 tasks that test the agent's ability to perform engineering work required to build and operate robotic systems, including control and perception algorithms, designing r...
A new hierarchical motion planning method for space redundant manipulators is proposed, integrating goal-biased RRT with sequential convex programming. The method generates smooth trajectories satisfying obstacle avoidance, end-effector line-of-sight constraints, and joint torque limits, converging in 17 and 18 iterations for static an...
The SMASH Team, led by Professor Ping LUO, won the silver medal in robot table tennis at the World Humanoid Robot Games. The team's autonomous humanoid table tennis system, SMASH, is the world's first to use onboard sensing to achieve consecutive strikes and rallies with human players.
Researchers trained AI on stick insect walking cycle to find optimal walking strategy, resulting in a six-legged robot that can navigate treacherous terrain and adapt to missing limbs. The approach allows for cheaper and faster robot production, enabling potential disaster response applications.
A new smartphone app called Mobilio uses AI, machine learning, and personalized audio cues to provide turn-by-turn directions, path guidance, and obstacle avoidance for people with blindness or low vision. The app completed outdoor navigation tasks 13% faster and reduced obstacle contact by 41% compared to Google Maps and a white cane.
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.
Researchers at Seoul National University have developed a novel approach using porous triply periodic minimal surface (TPMS) feet and deep reinforcement learning controller, which significantly reduces battery power consumption in quadruped robots. The solution reduces energy consumption by up to 6.2% while maintaining stable locomotion.
Researchers at MIT developed a new technique called VLASH that allows robots to predict their future position, enabling smoother motions and quicker reactions. This breakthrough doubles the speed of robots performing tasks like pick-and-place and boosts performance in dynamic activities.
A mechanical soft force sensor eliminates electronic components, allowing soft robots to sense and respond without power or signal processing. The sensor detects multi-axis forces and converts them directly into fluidic actuation.
The Robotic Surgery Center at KU Ansan Hospital has introduced the Da Vinci 5 robotic system, expanding its precision surgical capabilities. With its advanced features and ergonomic design, the system is expected to enhance patient safety and clinical outcomes.
The department has demonstrated outstanding clinical proficiency in robotic-assisted procedures and has been at the forefront of education and technical exchange. It plans to further expand training programs and integrate digital capabilities into clinical practice.
Researchers developed EleTac, a soft robotic gripper with high-resolution tactile sensing, to handle delicate objects. The gripper's innovative design enables it to adapt to various shapes and provide gentle forces, making it suitable for applications such as handling fruit, lab samples, and medical supplies.
A new robot mimics the movement of an inchworm using a soft muscle-like material, allowing it to navigate challenging environments. The robot can be used to inspect sewer pipes or explore the planet Mars without multiple actuators.
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 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.
A high-resolution model developed by University of Pennsylvania researchers shows that river levels once expected every 50 years now occur every few years due to climate change. The 1-in-100-year threshold marks a tipping point when flooding spreads rapidly across the urban landscape.
Recent advances in noninvasive neural decoding, deep learning, and shared autonomy are bringing BCI-controlled robots closer to real-world use. These systems can decode complex brain signals related to movement intention, allowing for more flexible and higher-dimensional robotic behaviors.
Researchers explore how next-gen AI and sensor-rich operating rooms can enable more precise, data-driven, personalized surgery. Advances in multimodal data integration, machine learning, and robotic systems could enhance situational awareness and intraoperative decision-making.
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.