Robohub.org
 

A variable stiffness fiber that self-heals


by
27 October 2016



share this:
img_4456_dxo_web

A group from Floreano Lab, EPFL and NCCR Robotics has today published their novel variable stiffness fibre with self-healing capability.

Soft “hardware” components are becoming more and more popular solutions within the field of robotics. In fact softness, compliance and foldability bring significant advantages to devices by allowing conformability and safe interactions with users, objects and unstructured environments. However for some applications, the softness of components adversely reduces the range of forces those devices can apply or sustain. An optimal solution would be having components able to vary their softness according to the needed task.

The fibre has a metal core, consisting of low melting point alloys (LMPA), which is contained within a pre-stretched silicone tube. At room temperatures the LMPA is a solid, thus, the fibre is stiff and behaves like a thin metal wire. But when an electrical current is passed through a copper wire coiled around the tube, the LMPA inner core is warmed above 62 oC and melts, thus, the fibre becomes up to 700 times softer and 400 times more deformable.

img_4462_dxo_web

The second advantage is that if the metallic core breaks it just needs to be heated and — voila! The fibre is fixed! And to top it off, the changing of states occurs in tens of seconds (depending on the current injected and the dimension of the LMPA core).

The fibre has a myriad of real-world applications in the fields of mobile robots, wearable devices and soft systems. Currently, the team is using the fibre to create multi-purpose foldable drones. In fact, the fibre can be morphed into different shapes that are preserved after cooling, ie the four arms of the drone can take different functional morphologies, i.e. deployed in a quadrotor-like configuration for aerial locomotion or bent towards the ground in a four-wheeled configuration for terrestrial locomotion.

img_4473_dxo_web

Future applications that the team is investigating include in endoscopes and other medical applications, where instruments need to be soft and pliable as they are exploring delicate body cavities, but then need to be able to penetrate resistive biological tissues (e.g. for a biopsy) once they have reached their desired location.

Reference

Tonazzini, A., Mintchev, S., Schubert, B., Mazzolai, B., Shintake, J. and Floreano, D. (2016), Variable Stiffness Fiber with Self-Healing Capability. Adv. Mater.. doi:10.1002/adma.201602580



tags: , , , ,


NCCR Robotics





Related posts :



Robot Talk Episode 136 – Making driverless vehicles smarter, with Shimon Whiteson

  05 Dec 2025
In the latest episode of the Robot Talk podcast, Claire chatted to Shimon Whiteson from Waymo about machine learning for autonomous vehicles.

Why companies don’t share AV crash data – and how they could

  01 Dec 2025
Researchers have created a roadmap outlining the barriers and opportunities to encourage AV companies to share the data to make AVs safer.

Robot Talk Episode 135 – Robot anatomy and design, with Chapa Sirithunge

  28 Nov 2025
In the latest episode of the Robot Talk podcast, Claire chatted to Chapa Sirithunge from University of Cambridge about what robots can teach us about human anatomy, and vice versa.

Learning robust controllers that work across many partially observable environments

  27 Nov 2025
Exploring designing controllers that perform reliably even when the environment may not be precisely known.

Human-robot interaction design retreat

  25 Nov 2025
Find out more about an event exploring design for human-robot interaction.

Robot Talk Episode 134 – Robotics as a hobby, with Kevin McAleer

  21 Nov 2025
In the latest episode of the Robot Talk podcast, Claire chatted to Kevin McAleer from kevsrobots about how to get started building robots at home.



 

Robohub is supported by:




Would you like to learn how to tell impactful stories about your robot or AI system?


scicomm
training the next generation of science communicators in robotics & AI


 












©2025.05 - Association for the Understanding of Artificial Intelligence