Wednesday 16 April 2025
Soft robots are increasingly being designed to mimic the flexibility and dexterity of living creatures, allowing them to navigate complex environments and interact with their surroundings in a more natural way. One key challenge in developing these robots is creating materials that can withstand the stresses and strains of repeated use while still maintaining their shape and function.
A team of researchers has made significant progress in this area by designing a new type of soft pneumatic actuator (SPA) that uses concentric rings to control its movement and force output. The SPA is essentially a flexible tube filled with air, which is inflated to varying pressures to achieve different levels of stiffness and shape.
The key innovation here is the use of stiffening elements – in this case, rings of silicone material – to limit the deformation of the tube as it expands and contracts. This allows the actuator to maintain its shape and generate consistent forces over a wide range of movements and loads.
To test the performance of their design, the researchers created a dataset of 22 different membrane configurations, each with varying thicknesses, ring radii, and other parameters. They then used machine learning algorithms to model the behavior of these membranes under different conditions, such as changes in pressure or load.
The results are impressive – the SPAs were able to generate forces over 100 Newtons (about the weight of a small child) while maintaining their shape and function over a wide range of movements. The models also accurately predicted the performance of the actuators under different conditions, allowing the researchers to optimize their design for specific tasks.
One potential application of this technology is in the development of soft robots that can be used to lift or manipulate objects in complex environments – such as in search and rescue operations or medical procedures. By using a combination of these SPAs and other sensors and actuators, it may be possible to create robots that can navigate through tight spaces and interact with their surroundings in a more natural way.
The use of machine learning algorithms to model the behavior of soft materials is also an important aspect of this research. By leveraging the power of AI to analyze complex data sets, researchers can gain valuable insights into the properties and behavior of these materials – insights that could be used to develop new technologies and applications in a wide range of fields.
Overall, this research represents an important step forward in the development of soft robots and their potential applications.
Cite this article: “Soft Robots Take Flight: Machine Learning Enables High-Force Actuators for Programmable Shape Morphing”, The Science Archive, 2025.
Soft Robots, Pneumatic Actuators, Machine Learning, Silicone Rings, Membrane Configurations, Force Output, Stiffness, Shape Control, Search And Rescue, Medical Procedures
