Articles tagged with Robotic Grippers
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.
A new robotic design uses vine-like structures to lift and grasp a variety of objects, including humans, with a gentler approach. The robot can snake around obstacles, squeeze through tight spaces, and even secure itself in a closed loop to create a sling.
Researchers at EPFL's CREATE Lab have developed bio-hybrid robots that use discarded crustacean shells to create a robotic manipulator, grippers, and a swimming robot. The devices combine the strength and flexibility of natural materials with synthetic components for sustainable design and reuse.
Researchers at Purdue University have developed fidget-controlled robots that utilize metastability to create soft robotic systems. These robots use bistable domes to perform tasks such as grasping and classifying objects, demonstrating the potential for physical systems to replace electronic components in challenging environments.
Researchers developed a bio-inspired bistable robotic gripper with tunable energy barrier, achieving rapid, compliant, and powerful grasping behavior. The gripper can adapt to different tasks and environments through dynamic energy barrier modulation, enabling efficient interaction with objects.
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.
Johns Hopkins engineers developed a pioneering prosthetic hand that can grip and grasp everyday objects like a human, using a hybrid design that combines rigid and soft robotics. The system achieves 99.69% accuracy in handling objects of varying textures and materials.
The research team developed a gripper (MOGrip) that can transfer multiple objects simultaneously, reducing process time by 34% and travel distance by 71%. Inspired by human multi-object grasping strategy, MOGrip features in-hand translation capability and decoupling links for simplified control.
Researchers at Tampere University have developed a non-electric touchpad that can sense force, area, and location of contact without electricity. The device is made of soft silicone and contains 32 channels, enabling precise detection of handwritten letters and multiple simultaneous touches.
A new system dubbed SonicSense allows robots to interpret the world through acoustic vibrations, giving them a richer ability to 'feel' and understand objects. The system, featuring a robotic hand with contact microphones, can identify materials, shapes, and recognize objects in complex environments.
Researchers developed ROSE, a soft robotic gripper that gently grasps objects using a unique 'wrinkling' phenomenon. The study demonstrates ROSE's effectiveness in picking up various crops, including strawberries and mushrooms, with high success rates.
Researchers at Singapore University of Technology and Design designed a vacuum-actuated hybrid soft gripper to handle delicate objects of varying sizes and shapes. The gripper features soft composite fingers and a palm, enabling wide grasping potential and adaptability to specific tasks.
Researchers at Uppsala University have developed an artificial tactile system that can detect pressure by touch in a similar way to the human nervous system. The technology has the potential to restore lost functionality to patients after a stroke, as well as enhance interactions between humans and robots.
The new metafluid can transition between Newtonian and non-Newtonian states, allowing for programmable viscosity and compressibility. The researchers demonstrated the fluid's capabilities in a hydraulic robotic gripper, picking up objects of varying weights without crushing them.
A temperature-sensitive prosthetic limb has been developed to improve amputee interactions and feelings of human connection. Researchers have created a device called MiniTouch that provides realistic and real-time thermal feedback, enabling amputees to discriminate between objects of different temperatures and materials.
A self-healing elastomer forms the flexible membrane of the gripper, which can heal from scratches and punctures in approximately nine minutes. The gripper's design enables recyclability, allowing for a sustainable option for universal grippers and soft robotics.
Researchers developed a new 3D inkjet printing system that works with a wider range of materials, including slower-curing materials. The system utilizes computer vision to automatically scan the print surface and adjust the amount of resin deposited in real time.
A new technology enables the printing of complex robots with soft, elastic, and rigid materials in one go. This allows for the creation of delicate structures and parts with cavities as desired.
Researchers at North Carolina State University have developed a robotic gripping device that can handle ultrasoft, ultrathin, and heavy objects with excellent balance of strength, precision, and gentleness. The design uses kirigami and can be fabricated from biodegradable materials.
Researchers at UC San Diego developed a robotic hand that can rotate objects solely through touch without relying on vision. The system uses low-cost, binary signals from multiple sensors to detect object contact and perform precise rotations.
ROSE, a novel soft gripping robotic gripper, boasts remarkable durability, scalability and effectiveness in handling fragile objects, with potential applications in harvesting, sorting and cluttered environments.
Researchers at the University of Cambridge designed a soft robotic hand that can grasp a range of objects using passive movement and tactile sensors. The hand successfully grasped 11 of 14 objects in tests, including a peach, computer mouse, and roll of bubble wrap, demonstrating its ability to predict when it might drop an object.
Researchers developed a robotic finger with high-resolution sensors that capture data along the entire length of each finger. The three-fingered robotic hand can identify objects after just one grasp, with 85% accuracy, using tactile sensing and machine-learning algorithms.
Researchers from Singapore University of Technology and Design developed a new reconfigurable workspace soft robotic gripper that can pick and place a wide range of consumer items. The RWS gripper's adaptive capabilities make it particularly useful in logistics and food industries where robotic automation is crucial.
A team of researchers developed a new method for 3D-printing microrobots with multiple component modules inside the same microfluidic chip. The 'assembly line' approach allowed for the combination of various modules, such as joints and grippers, into a single device. This innovation may help realize the vision of microsurgery performed...
Researchers developed a compact robotic finger with adjustable stiffness to withstand physical impacts and mimic human finger dexterity. The finger mechanism is based on gear transmission and mechanically passive compliance, providing an advantage in terms of reliability, ease of manufacture, and maintenance.
Researchers designed a soft, jellyfish-like gripper that uses entangled tentacles to grasp and hold heavy, oddly shaped objects. The gripper's strength comes from its ability to entangle itself with the object, increasing the hold with each contact.
Researchers at Harvard University have developed inflatable actuators that can bend, twist, and move in complex ways using origami-inspired designs. The actuator's bistable origami blocks allow it to perform up to eight different motions with a single pressure source.
MIT researchers develop an interactive design pipeline enabling users to create customized robotic hands with tactile sensors. The platform streamlines the process, allowing users to adjust palm and fingers and integrate tactile sensors, resulting in complex tasks like picking delicate items or using tools being performed flawlessly.
Researchers developed a novel wearable soft robotic armband that conveys artificial sensations of touch to prosthetic hands, enabling users to control multiple grasp functions simultaneously. The study showed improved time efficiency and precision in transporting objects, with haptic feedback being crucial for tasks.
Researchers developed soft manipulators based on pneu-nets, mimicking biological systems like elephant trunks and octopus tentacles. These structures can grasp and manipulate soft objects with increased flexibility.
Researchers at Stanford University have created a robotic hand with a gecko-inspired grip that can handle both delicate and heavy objects. The 'farmHand' gripper uses gecko-adhesive pads and has a unique finger design to enable both dexterity and strength.
The 'Rolling Fingers' robotic hand can move objects in a single grasp without needing two arms, simplifying tasks for robots. Its adaptive fingers and rotating skin enable safe manipulation of non-rigid objects, making it suitable for industrial and clinical applications.
A partially-compliant robot hand using a Crossed Flexural Hinge (CFH) was developed to increase lifting power while minimizing damage in collisions. The CFH-jointed robot hand demonstrated 46.7% more shock absorption than a pin joint-oriented robotic hand and could hold objects weighing up to four kilograms.
A novel soft tactile sensor with skin-comparable characteristics has been developed for robots, allowing them to grasp fragile objects and thread needles. The sensor decouples external forces into normal and shear components, providing accurate measurements.
Researchers have designed a smart electronic skin and medical robotic hand that can assess vital diagnostic data using a newly invented rubbery semiconductor with high carrier mobility. The material is scalable for manufacturing and retains electrical performance even when stretched by 50%.
A new robot hand with a dynamic grip can adjust its stiffness to absorb shocks, keeping objects intact during collisions. This technology is valuable for industries like automotive and electronics packaging, enhancing worker safety and machine performance.
Researchers develop new approach combining individual finger control and automation to improve grasping and manipulation for amputees. The technology uses machine learning and sensor data to interpret user intention and automate object grasp.
Researchers at Stanford University have developed an electronic glove with sensors that can detect pressure intensity and direction, allowing a robotic hand to perform tasks like lifting eggs and handling delicate objects without crushing them. The technology has potential applications in robot-assisted surgery and other fields where p...
An interdisciplinary team is creating a living pathway from the robot's touch sensation to the user's brain to help amputees control the robotic hand. The researchers aim to regenerate the sensation of touch in an artificial limb using living residual neural pathways.
Researchers at the University of Houston have developed a new form of stretchable electronics that can serve as an artificial skin, allowing a robotic hand to sense temperature differences. The breakthrough enables the creation of biomedical devices such as health monitors and medical implants with improved functionality.
A company's failed attempt to bring jamming-based robotic gripper technology to market provides valuable insights into the challenges of product development and commercialization. The authors share their research and product design efforts, highlighting key factors that influenced customer purchasing decisions.
Researchers have created a three-fingered soft robotic hand with embedded optical sensors, allowing it to detect forces of less than a tenth of a newton and determine where its fingertips are in contact. The new stretchable optical sensing material could be used in a soft robotic skin for even more feedback.
Engineers at MIT have developed a model that predicts the force needed for robotic grippers to adjust their grasp on an object by interacting with the environment. This approach, called extrinsic dexterity, enables robots to perform more complex maneuvers without needing expensive and complex hand designs.