Tag Archives: Soft Robots

3-D Printed Skin Improves Dexterity

The healthcare industry has always had a longstanding relationship with soft robotics. Soft robots are increasingly making their presence felt by assisting physicians in surgical procedures and turning major surgeries into minimally invasive procedures. With more physicians using soft robots that can feel and respond to stimuli, they can be substantially more precise, thereby posing a vastly lower risk of damaging sensitive organs and soft tissues with the wrong amounts of pressure.

Soft robots are more responsive to various stimuli, making them substantially more delicate and refined grippers for machines. They allow researchers to pick up delicate specimens deep underwater, or make complicated repairs outside the ISS. It is essential to have robots with dexterous and easy-to-control extremities. Their pressure-sensitive grippers can detect if they are holding a soft squid or a tiny metal part. They can adjust their grip accordingly, thereby preventing dangerous and time-consuming mistakes.

However, while emulating the sense of touch, researchers have had limited success with tactile-sensing technology, especially when fine-tuning dexterity. This is now changing with researchers from the University of Bristol creating the bionic sense of touch. Researchers from the Department of Engineering Maths are using 3-D printed papillae mesh on the under-surface of a compliant skin.

Scientists, in an empirical study, have made substantial comparisons of the performance of a bionic fingertip against neural recordings made of the sense of human touch. Not only have they published their findings in a Journal of the Royal Society Interface, they have also described the creation of an artificial biometric tactile sensor, which they call the TechTip. Their creation can behave dynamically just like human skin does, and provide sensory responses. In simple words, the artificial fingertip mimics human nerve signals.

The robotic hand has a 3-D printed tactile fingertip on its finger. A black flexible 3-D printed skin covers the white rigid back of the fingertip. The construction is similar to the dermal-epidermal interface of the skin and is backed by a mesh consisting of dermal papillae and intermediate biometric ridges. The dermal papillae comprise markers tipping the inner pins.

Scientists constructed the papillae on advanced 3-D printers with the capability of mixing hard and soft materials to emulate effects and textures similar to human biology.

The scientists claim their work uncovers the complex internal structure of the human skin and recreates the human sense of touch. For them, this represents an exciting development in the field of soft robotics. They have been able to 3-D print an artificial tactile skin that can lead to robots that are more dexterous. They can also significantly improve the performance of prosthetic hands, providing them with an in-built sense of touch.

According to scientists at the University of Bristol, a 3-D printed tactile fingertip can produce signals from its artificial nerves. These signals are similar to the recordings from real tactile neurons. They claim human tactile nerves transfer signals from numerous mechanoreceptors or nerve endings. These indicate the shape and pressure of contact. In their work, the scientists claim to have tested their 3-D printed artificial fingertip, and they found the same ridged profiles and a startlingly close match to the recorded neural data.

Soft Robots Mimic Biological Movements

At Harvard University, researchers have developed a model for designing soft robots. The special features of these robots include bending as a human index finger does and twisting like a thumb when a single pressure source powers the robots.

For long, scientists have followed a process of trial and error for designing a soft robot that moves organically—twisting as a human wrist does, or bending just like a finger. Now, at the Wyss Institute for Biologically inspired Engineering and the Harvard JA Paulson School of Engineering and Applied Sciences, researchers have developed a method for automatically designing soft actuators that are based on the desired movement. They have published their findings in the Proceedings of the National Academy of Sciences.

To perform the biologically inspired motions, the researchers turned to mathematics modeling for optimizing the design of the actuator. According to Katia Bertoldi, Associate Professor and coauthor of the paper, now they do not design the actuators empirically. The new method allows them to plug in a motion and the model gives them the design of the actuator that will achieve that motion.

Although the design of a robot that can bend as a finger or a knee does can seem simple, it is actually an incredibly complex process in practice. The complications of the design stems from the fact that one single actuator cannot produce the complex motions necessary. According to the first author of the paper, Fionnuala Connolly, who is also a graduate student at SEAS, the design requires sequencing the actuator segments. Each of them performs a different motion, with only a single input actuating them all.

The team uses fiber-reinforced, fluid-powered actuators. Their method uses mathematical modeling for optimizing the design of the actuators, which perform a certain motion. With their method, the team was able to design soft robots that bend and twist just as human fingers and thumbs do.

SEAS have developed an online, open-source resource that provides the new methodology in the form of a Soft Robotic Toolkit. This will assist educators, researchers, and budding innovators in designing, fabricating, modeling, characterizing, and controlling their own soft robots.

The robotics community has long been interested in embedding flexible materials such as cloth, paper, fiber, and other particles including soft fluidic actuators, which consist of elastomeric matrices. These are lightweight, affordable, and easily customizable to a given application.

These multi-material fluidic actuators are interesting as the robotics community can rapidly fabricate them in a multi-step molding process. Only a simple control input such as from a pressurized fluid achieves the combinations of extension, contraction, twisting, and bending. Compared to the existing designs, new design concepts are using fabrication approaches and soft materials for improving the performance of these actuators.

For instance, motivating applications are using soft robotics such as heart assist devices and soft robotic gloves for defining motion and forcing profile requirements. It is possible to embed mechanical intelligence within these soft actuators for achieving these performance requirements with simple control inputs. The challenge lies in the nonlinear nature of the large bending motions the hyper-elastic materials produce, which make it difficult to characterize and predict their behavior.