Is cracking your knuckles really bad for them? It doesn't actually cause arthritis. Cracking your knuckles and joints may be rude, but does it actually mess with your joints? Breakthroughs, discoveries, and DIY tips sent every weekday. It's an age-old tale: A knuckle-cracking lover and hater enter a room.

Fixed degree-of-freedom (DoF) loading mechanisms often suffer from excessive actuators, complex control, and limited adaptability to dynamic tasks. This study proposes an innovative mechanism of underactuated metamorphic loading manipulators (UMLM), integrating a metamorphic arm with a passively adaptive gripper. The metamorphic arm exploits geometric constraints, enabling the topology reconfiguration and flexible motion trajectories without additional actuators. The adaptive gripper, driven entirely by the arm, conforms to diverse objects through passive compliance. A structural model is developed, and a kinetostatics analysis is conducted to investigate isomorphic grasping configurations. To optimize performance, Particle-Swarm Optimization (PSO) is utilized to refine the gripper's dimensional parameters, ensuring robust adaptability across various applications. Simulation results validate the UMLM's easily implemented control strategy, operational versatility, and effectiveness in grasping diverse objects in dynamic environments. This work underscores the practical potential of underactuated metamorphic mechanisms in applications requiring efficient and adaptable loading solutions. Beyond the specific design, this generalized modeling and optimization framework extends to a broader class of manipulators, offering a scalable approach to the development of robotic systems that require efficiency, flexibility, and robust performance.

Tactile information effectively enables faster training and better task performance for learning-based in-hand manipulation. Existing approaches are validated in simulated environments with a large number of tactile sensors. However, attaching such sensors to a real robot hand is not applicable due to high cost and physical limitations. To enable real-world adoption of tactile sensors, this study investigates the impact of tactile sensors, including their varying quantities and placements on robot hands, on the dexterous manipulation task performance and analyzes the importance of each. Through empirically decreasing the sensor quantities, we successfully find an optimized set of tactile sensors (21 sensors) configuration, which keeps over 93% task performance with only 20% sensor quantities compared to the original set (92 sensors) for the block manipulation task, leading to a potential reduction of over 80% in sensor manufacturing and design costs. To transform the empirical results into a generalizable understanding, we build a task performance prediction model with a weighted linear regression algorithm and use it to forecast the task performance with different sensor configurations. To show its generalizability, we verified this model in egg and pen manipulation tasks and achieved an average prediction error of 3.12%.

Knuckles, right, appears in the Sega Genesis video game'Sonic & Knuckles.' Fans of Sonic The Hedgehog are well acquainted with Knuckles, the red echidna made popular through a series of video games produced by Sega. Recently, the character has taken on a whole new persona online in the form of Ugandan Knuckles. Not only has the character morphed into its own meme, complete with catchphrase, it has devolved into an unfortunate fixture of Internet memes -- a troll that harasses other online players and spews racist phrases. Here is what you need to know about Knuckles, and his second life under his Ugandan form.

The quest for Artificial Intelligence is a field which has both fascinated and terrified mankind for decades. Books like Isaac Asimov's "Robot" series and Douglas Adams' "Hitchiker's Guide to the Galaxy" envision dystopian futures in which Intelligent machines have become indispensable to human life, whilst films like "The Terminator" and "Ex Machina" explore a darker side of AI, where machines become a threat to mankind's very survival. So what is the truth? Do we get C-3PO, or do we get Ultron? Thankfully, that is a debate for another generation to grapple with.

An electric glove which can convert sign language into text messages has been unveiled by scientists. The $100 (£77) device will will allow deaf people to instantly send messages to those who don't understand sign language, according to its inventors. Researchers fitted a standard sports glove with nine flexible strain sensors which react when a user bends their fingers to create the new device. The device consists of a sports glove which has been fitted with nine stretchable sensors positioned over the knuckles. When a user bends their fingers or thumb to sign a letter, the sensors stretch, which causes an electrical signal to be produced.