View all newsletters
Receive our newsletter – data, insights and analysis delivered to you
  1. News
March 1, 2018

New 3D printing method to insert sensors in soft robots

Researchers at the Harvard John A Paulson School of Engineering and Applied Sciences (SEAS) and the Wyss Institute for Biologically Inspired Engineering in the US have developed a new approach to generate robotic actuators with integrated sensing capabilities.

Researchers at the Harvard John A Paulson School of Engineering and Applied Sciences (SEAS) and the Wyss Institute for Biologically Inspired Engineering in the US have developed a new approach to generate robotic actuators with integrated sensing capabilities.

With the new manufacturing platform, the soft robots will be able to sense movement, pressure, touch, as well as temperature.

To address the concerns with existing rigid electronics, the team created a conductive ink that is based on organic ionic liquid and can easily be 3D-printed within the soft elastomer matrices used in the majority of robotic actuators.

The researchers adopted an established method called embedded 3D printing designed for fast and optimised incorporation of different features and materials in a single soft body.

Combination of this method and the new ink is intended to fuse soft sensing and actuation within one integrated soft robotic system.

“We open new avenues to device design and fabrication that will ultimately allow true closed-loop control of soft robots.”

SEAS former postdoctoral fellow and researcher Michael Wehner said: “To date, most integrated sensor / actuator systems used in soft robotics have been quite rudimentary.

“By directly printing ionic liquid sensors within these soft systems, we open new avenues to device design and fabrication that will ultimately allow true closed-loop control of soft robots.”

The researchers tested the sensors by printing a soft robotic gripper with three soft fingers and embedded with various contact sensors. It was then explored for the ability to sense inflation pressure, curvature, contact and temperature.

Over the coming months, the team plans to train the new devices using machine learning to grasp objects of different size, shape, surface texture, and temperature.

Related Companies

NEWSLETTER Sign up Tick the boxes of the newsletters you would like to receive. The top stories of the day delivered to you every weekday. A weekly roundup of the latest news and analysis, sent every Friday. The medical device industry's most comprehensive news and information delivered every month.
I consent to GlobalData UK Limited collecting my details provided via this form in accordance with the Privacy Policy
SUBSCRIBED

THANK YOU