Going Wireless Is Not Just For Phones

Soft robots are made of flexible materials such as fluids, gels, or elastomers that allow the machine to change shape easily. These robots can be utilized in many different ways such as industrial or aerospace applications as well as in the medical field as surgical assistance tools. However, traditional soft robots require line-of-sight heating, meaning that they need to be directly heated by wires or lasers. This can prove to be an issue if a robot needs to enter a blocked environment like inside a pipe.

A team of researchers led by Swarun Kumar, associate professor of electrical and computer engineering, developed the Wireless Actuation for Soft Electronics-free Robots (WASER) platform where the soft robot can be controlled in a non-line-of-sight context using wireless energy. The signal they use can carry through blockages like wood and walls, similar to Wi-Fi signals that we use for cell phones.

The material the team used is called liquid crystal elastomer, which functions similarly to a muscle as it shrinks and contracts when heat is applied. However, liquid crystal elastomer is not a material that is effectively heated with wireless energy. 

“Essentially, what we did in this project was apply other materials on top of this soft robot liquid crystal elastomer to make heating more efficient,” says Yiwen Song, a third-year Ph.D. student in electrical and computer engineering. 

The two main challenges the team faced were on the wireless front and the materials front.

“We used a blind beamforming algorithm to power and focus the wireless energy onto the desired area of the robot,” Song says. For materials, they combined liquid metal with the elastomer which would allow the robots to harvest the wireless energy and convert it into shape change.

In the future, the team hopes to figure out ways to make heating more efficient so that the system requires less power to activate. Additionally, by investigating a stronger targeting method, these robots will hopefully be able to make more complex movements. Together, the end goal is to produce energy-efficient, highly precise soft robots. 

The team of researchers included Jingxian Wang, Yiwen Song, Mason Zadan, Yuyi Shen, Vanessa Chen, Carmel Majidi, and Swarun Kumar.