stub Engineers Develop Soft Robotic Hand Capable of Playing Nintendo - Unite.AI
Connect with us

Robotics

Engineers Develop Soft Robotic Hand Capable of Playing Nintendo

Published

 on

Researchers and engineers at the University of Maryland have created a 3D-printed soft-robotic hand that is able to play Nintendo’s Super Mario Bros. 

In what is an incredible advancement in the agility of robotic hands, the research was presented in Science Advances.

The field of soft robotics focuses on flexible and inflatable robots that are powered with water or air, while traditional robots are powered through electricity. There has been an increased interest in soft robotics due to their safety and adaptability, which has led to them often being used for prosthetics and medical devices. However, until the new research, it has been difficult to control the fluids that enable the robots to bend and move.

The research team was led by University of Maryland assistant professor of mechanical engineering Ryan D. Sochol. The team’s big breakthrough came when they were able to 3D print fully assembled soft robots with integrated fluidic circuits, and all of this was able to be done in one single step.

Joshua Hubbard is co-first author.

“Previously, each finger of a soft robotic hand would typically need its own control line, which can limit portability and usefulness,” explains Hubbard. “But by 3D printing the soft robotic hand with our integrated fluidic transistors, it can play Nintendo based on just one pressure input.”

Image: University of Maryland

Demonstrating the Robot

The team demonstrated the soft robotic hand by designing an integrated fluidic circuit that enabled it to operate in response to a single control pressure. By applying a low pressure, the team could make the first finger press the Nintendo controller to make Mario walk. By applying high pressure, Mario would jump. 

The hand relied on a set program that autonomously switched between off, low, medium, and high pressures, and it was able to operate the Nintendo controller successfully and complete the first level of the game in less than 90 seconds.

Ruben Acevedo is a recent Ph.D. graduate and co-first author of the study. 

“Recently, several groups have tried to harness fluidic circuits to enhance the autonomy of soft robots,” said Acevedo, “but the methods for building and integrating those fluidic circuits with the robots can take days to weeks, with a high degree of manual labor and technical skill.”

3D Printing

The team relied on “PolyJet 3D Printing,” which has many layers of multi-material ‘inks’ stacked on top of one another in 3D.

Kristen Edwards is the study’s co-author. 

“Within the span of one day and with minor labor, researchers can now go from pressing start on a 3D printer to having complete soft robots — including all of the soft actuators, fluidic circuit elements, and body features — ready to use,” said Edwards

Choosing Mario was not just a decision based on fun, but it actually served as an accurate way of measuring the hand’s agility. The video game’s timing and level make-up are already established, with a single mistake ending the game. This provided a new way of evaluating the robot. 

Other Research Advancements and Open Access

The team’s research paper also detailed terrapin turtle-inspired soft robots, which were all printed at UMD’s Terrapin Works 3D Printing Hub.

The team’s strategy is also open source, and the paper is open access for anyone to read. The team also linked their supplementary materials to a GitHub, and it includes all of the electronic design files.

“We are freely sharing all of our design files so that anyone can readily download, modify on demand, and 3D print — whether with their own printer or through a printing service like us — all of the soft robots and fluidic circuit elements from our work,” said Sochol. “It is our hope that this open-source 3D printing strategy will broaden accessibility, dissemination, reproducibility, and adoption of soft robots with integrated fluidic circuits and, in turn, accelerate advancement in the field.”

The team is now looking at how their technique can be used for biomedical applications like rehabilitation devices, surgical tools, and customizable prosthetics.

 

Alex McFarland is a tech writer who covers the latest developments in artificial intelligence. He has worked with AI startups and publications across the globe.