Say More Look Up Versus Mashable's Best: E-readers, robovacs, laptops, earbuds, smart home and more Mashable Selects Creator Playbook In My Bag Trending Now Back to School Good Connection: Uplifting stories for a digital age Switch Off Mashable Voices All Series Loop earplugs are actually worth it -- here's how to choose the right pair What you need to know about the earplugs sold during Harry Styles' Madison Square Garden residency. Bethany Allard is a Los Angeles-based shopping reporter at Mashable covering beauty tech, dating, sex and relationships, and headphones. That basically means she puts her hair through a lot, scrolls through a lot of dating apps, and rotates through a lot of different headphones. In addition to testing out and rounding up the best products, she also covers deals for Mashable, paying an especially obsessive amount of attention to Apple deals and prices. That knowledge comes in handy when she's covering shopping holidays like Prime Day and Black Friday, which she's now done for three years at Mashable.

What makes'The Pitt' so horrifyingly realistic? We asked the show's makeup and prosthetic pros. 'Depending on the procedure, it can vary between two and nine weeks to build.' More information Adding us as a Preferred Source in Google by using this link indicates that you would like to see more of our content in Google News results. 'The Pitt' features a level of realism not previously seen on screen.

Plastic-Free Drip Coffee Is a Holy Grail. Microplastics are in everything, especially your coffee. A new generation of plastic-free coffee brewers is trying to change this. The era of plastic-free drip coffee has finally arrived. It couldn't come soon enough. Drip coffee is my first true love when it comes to caffeine. But sadly, my first love is hopelessly addicted to plastic. From the very first Mr. Coffee machines in the 1970s, nearly every drip coffee maker on the market, including many of my favorite drip coffee makers, has included plastic at some point in the brewing process. But plastic, as we're now learning, can leach tiny particles called microplastics into coffee or water, which you then happily drink in your morning cup.

This paper presents a novel underactuated adaptive robotic hand, Hockens-A Hand, which integrates the Hoeckens mechanism, a double-parallelogram linkage, and a specialized four-bar linkage to achieve three adaptive grasping modes: parallel pinching, asymmetric scooping, and enveloping grasping. Hockens-A Hand requires only a single linear actuator, leveraging passive mechanical intelligence to ensure adaptability and compliance in unstructured environments. Specifically, the vertical motion of the Hoeckens mechanism introduces compliance, the double-parallelogram linkage ensures line contact at the fingertip, and the four-bar amplification system enables natural transitions between different grasping modes. Additionally, the inclusion of a mesh-textured silicone phalanx further enhances the ability to envelop objects of various shapes and sizes. This study employs detailed kinematic analysis to optimize the push angle and design the linkage lengths for optimal performance. Simulations validated the design by analyzing the fingertip motion and ensuring smooth transitions between grasping modes. Furthermore, the grasping force was analyzed using power equations to enhance the understanding of the system's performance.Experimental validation using a 3D-printed prototype demonstrates the three grasping modes of the hand in various scenarios under environmental constraints, verifying its grasping stability and broad applicability.

As robotics advances toward integrating soft structures, anthropomorphic shapes, and complex tasks, soft and highly stretchable mechanotransducers are becoming essential. To reliably measure tactile and proprioceptive data while ensuring shape conformability, stretchability, and adaptability, researchers have explored diverse transduction principles alongside scalable and versatile manufacturing techniques. Nonetheless, many current methods for stretchable sensors are designed to produce a single sensor configuration, thereby limiting design flexibility. Here, we present an accessible, flexible, printing-based fabrication approach for customizable, stretchable sensors. Our method employs a custom-built printhead integrated with a commercial 3D printer to enable direct ink writing (DIW) of conductive ink onto cured silicone substrates. A layer-wise fabrication process, facilitated by stackable trays, allows for the deposition of multiple liquid conductive ink layers within a silicone matrix. To demonstrate the method's capacity for high design flexibility, we fabricate and evaluate both capacitive and resistive strain sensor morphologies. Experimental characterization showed that the capacitive strain sensor possesses high linearity (R^2 = 0.99), high sensitivity near the 1.0 theoretical limit (GF = 0.95), minimal hysteresis (DH = 1.36%), and large stretchability (550%), comparable to state-of-the-art stretchable strain sensors reported in the literature.

Robotic systems' mobility is constrained by power sources and wiring. While pneumatic actuators remain tethered to air supplies, we developed a new actuator utilizing light energy. Inspired by nocturnal animals' eyes, we designed a bilayer soft actuator incorporating Laser-Induced Graphene (LIG) on the inner surface of a silicone layer. This design maintains silicone's transparency and flexibility while achieving 54% faster response time compared to conventional actuators through enhanced photothermal conversion.

Recent research has seen notable progress in the development of linkage-based artificial hands. While previous designs have focused on adaptive grasping, dexterity and biomimetic artificial skin, only a few systems have proposed a lightweight, accessible solution integrating tactile sensing with a compliant linkage-based mechanism. This paper introduces OPENGRASP LITE, an open-source, highly integrated, tactile, and lightweight artificial hand. Leveraging compliant linkage systems and MEMS barometer-based tactile sensing, it offers versatile grasping capabilities with six degrees of actuation. By providing tactile sensors and enabling soft grasping, it serves as an accessible platform for further research in tactile artificial hands.

This paper introduces a new method for estimating the penetration of the end effector and the parameters of a soft body using a collaborative robotic arm. This is possible using the dimensionality reduction method that simplifies the Hunt-Crossley model. The parameters can be found without a force sensor thanks to the information of the robotic arm controller. To achieve an online estimation, an extended Kalman filter is employed, which embeds the contact dynamic model. The algorithm is tested with various types of silicone, including samples with hard intrusions to simulate cancerous cells within a soft tissue. The results indicate that this technique can accurately determine the parameters and estimate the penetration of the end effector into the soft body. These promising preliminary results demonstrate the potential for robots to serve as an effective tool for early-stage cancer diagnostics.

Many robotic hands currently rely on extremely dexterous robotic fingers and a thumb joint to envelop themselves around an object. Few hands focus on the palm even though human hands greatly benefit from their central fold and soft surface. As such, we develop a novel structurally compliant soft palm, which enables more surface area contact for the objects that are pressed into it. Moreover, this design, along with the development of a new low-cost, flexible illumination system, is able to incorporate a high-resolution tactile sensing system inspired by the GelSight sensors. Concurrently, we design RObotic Modular Endoskeleton Optical (ROMEO) fingers, which are underactuated two-segment soft fingers that are able to house the new illumination system, and we integrate them into these various palm configurations. The resulting robotic hand is slightly bigger than a baseball and represents one of the first soft robotic hands with actuated fingers and a passively compliant palm, all of which have high-resolution tactile sensing. This design also potentially helps researchers discover and explore more soft-rigid tactile robotic hand designs with greater capabilities in the future. The supplementary video can be found here: https://youtu.be/RKfIFiewqsg

In recent years, the gripping use of unmanned aerial vehicles (UAVs) has emerged as a new trending research direction [1, 2]. However, the grabbing scenes in the open world are very complex, which leads to the development of robotic grasping systems with advanced cognitive and adaptable grasping capabilities. To achieve high-level cognitive abilities, reinforcement learning embodiment is studied[3, 4]. In [3], Scalable Deep Reinforcement Learning is used to handle large amounts of off-policy image data for complex tasks like grasping. However, RL-based embodiment has posed challenges in terms of generalization capability, sample-effectiveness capability, and profound reasoning capability, especially in dynamic and uncertain real environments. Recently, Large multimodal models (LMMs), such as MiniGPT-4 [5] and LLaVA [6], have exhibited impressive performance in the domains of natural instruction-following and visual cognition. Therefore, LMMs are integrated with the physical world in the embodied agent. Apart from RL algorithms for specific tasks, LMMs-based agents have generalization capabilities [7, 8] though fine-tune methods, such as human demonstrations [9], vision-language cross-modal connector[10], ever-growing skill library [11] and so on. On-policy (RL) algorithms face challenges in terms of sample efficiency.