This 3D printed gripper doesn’t need electronics to function

Researchers at the University of California San Diego, in collaboration with the BASF corporation, have developed a remarkable soft robotic gripper that boasts unique features. This gripper is 3D printed in one piece and does not require any electronics to function effectively.

The team’s objective was to create a soft gripper that could be used immediately after being 3D printed, complete with built-in gravity and touch sensors. The result is a gripper capable of picking up, holding, and releasing objects, a feat not achieved by any gripper before.

The gripper’s design incorporates a series of valves that enable it to grip upon contact and release at the right moment. Yichen Zhai, the leading author of the paper detailing the research, explains that by simply turning the gripper horizontally, a change in airflow triggers the release of the object held by its two fingers.

One of the remarkable aspects of this gripper is its fluidic logic, allowing it to remember when it has grasped an object and is holding onto it. When it senses the weight of the object pushing to the side as it rotates horizontally, it intuitively releases the object.

Soft robotics has great potential for safe human-robot interactions and delicate object handling. This gripper can be mounted on a robotic arm for various industrial manufacturing applications, such as food production and handling fruits and vegetables. It can also be used in research and exploration tasks. Furthermore, it can operate untethered, requiring only a bottle of high-pressure gas as its power source.

To overcome common issues faced with 3D-printed soft robots, such as stiffness, leaks, and the need for extensive post-processing and assembly, the researchers developed a new 3D printing method. Their innovative approach involves the printer nozzle tracing a continuous path through each layer, much like drawing a picture without lifting the pencil off the page. This method significantly reduces the likelihood of leaks and defects in the printed piece.

Additionally, the new printing method allows for the creation of thin walls, as small as 0.5 millimeters thick. This, in turn, results in a softer and more deformable structure, as the complex, curved shapes enable a higher range of deformation. The researchers based their method on the Eulerian path in graph theory, ensuring consistent printing of functional pneumatic soft robots with embedded control circuits.

This groundbreaking soft robotic gripper represents a significant step forward in robotics, with potential applications in various industries and research fields.

Posted in

Aihub Team

Leave a Comment





AI and Virtual Assistants: AI-driven virtual assistants, chatbots, and voice assistants for personalized user interactions.

AI and Business Process Automation: AI-powered automation of repetitive tasks and decision-making in business processes.

AI and Social Media: AI algorithms for content recommendation, sentiment analysis, and social network analysis.

AI for Environmental Monitoring: AI applications in monitoring and protecting the environment, including wildlife tracking and climate modeling.

AI in Cybersecurity: AI systems for threat detection, anomaly detection, and intelligent security analysis.

AI in Gaming: The use of AI techniques in game development, character behavior, and procedural content generation.

AI in Autonomous Vehicles: AI technologies powering self-driving cars and intelligent transportation systems.

AI Ethics: Ethical considerations and guidelines for the responsible development and use of AI systems.

AI in Education: AI-based systems for personalized learning, adaptive assessments, and intelligent tutoring.

AI in Finance: The use of AI algorithms for fraud detection, risk assessment, trading, and portfolio management in the financial sector.

AI in Healthcare: Applications of AI in medical diagnosis, drug discovery, patient monitoring, and personalized medicine.

Robotics: The integration of AI and robotics, enabling machines to perform physical tasks autonomously.

Explainable AI: Techniques and methods for making AI systems more transparent and interpretable

Reinforcement Learning: AI agents that learn through trial and error by interacting with an environment

Computer Vision: AI systems capable of interpreting and understanding visual data.

Natural Language Processing: AI techniques for understanding and processing human language.

Deep Learning: The advancement of deep neural networks and their applications in various domains.

The Biggest Lie In Protest

Protest Strategies For Beginners

Top 10 Tips To Grow Your Tech

Microsoft announces native Teams

Oppo working Find N Fold and Find

NASA scrubs second Artemis 1 launch

Lunar demo mission to provide “stress test” for NASA’s Artemis

Italian microsatellite promises orbital photo bonanza after

Uber drivers at record high as people record high as people as people

Tension between China and Taiwan has risen and what happens what happens

The ride-hailing app had been facing a driver shortage driver shortage

The meteoric rise of AMTD Digital’s shares has been likened been likened

THE BEST WINTER VACATION SPOTS IN THE USA