Harvard Researchers Develop Novel 3D Printing Method to Give Soft Robotic Gripper the Ability to Sense Its Surroundings

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Soft robotics has turned the idea of robots only being made of hard, rigid parts on its tail, and pairing the technology with 3D printing has led to some remarkable innovations, including soft hydrogel robots that are nearly invisible and the world’s first autonomous soft robot. This last was developed by researchers at Harvard University, from the Wyss Institute for Biologically Inspired Engineering and the John A. Paulson School for Engineering and Applied Sciences (SEAS).

Now, researchers from both SEAS and Wyss have developed a novel 3D printing method that gives soft robots sensing capabilities.

[Image: Ryan L. Truby, Harvard University]

These researchers have built other soft robots that can swim through liquid, crawl, grasp delicate objects, and help a heart keep beating, but this is the first one that can sense and respond to its surroundings.

Ryan L. Truby, a recent PhD graduate at SEAS, said, “Our research represents a foundational advance in soft robotics. Our manufacturing platform enables complex sensing motifs to be easily integrated into soft robotic systems.”

The team was inspired by the sensory capabilities of human bodies, and developed a platform to create soft robots that contain embedded sensors within actuators, which allow the robot to actually sense touch, movement, pressure, and temperature.

The researchers published a paper on their work, titled “Soft Somatosensitive Actuators via Embedded 3D Printing,” in the journal Advanced Materials; co-authors include Truby; former postdoctoral fellow at SEAS Michael Wehner; Abigail K. Grosskopf; Daniel M. Vogt; Sebastien G. M. Uzel; Robert J. Wood, the Charles River Professor of Engineering and Applied Sciences at SEAS; and Jennifer A. Lewis, the Hansjorg Wyss Professor of Biologically Inspired Engineering at SEAS and Core Faculty Member of the Wyss Institute.

The abstract reads, “Humans possess manual dexterity, motor skills, and other physical abilities that rely on feedback provided by the somatosensory system. Herein, a method is reported for creating soft somatosensitive actuators (SSAs) via embedded 3D printing, which are innervated with multiple conductive features that simultaneously enable haptic, proprioceptive, and thermoceptive sensing. This novel manufacturing approach enables the seamless integration of multiple ionically conductive and fluidic features within elastomeric matrices to produce SSAs with the desired bioinspired sensing and actuation capabilities. Each printed sensor is composed of an ionically conductive gel that exhibits both long-term stability and hysteresis-free performance. As an exemplar, multiple SSAs are combined into a soft robotic gripper that provides proprioceptive and haptic feedback via embedded curvature, inflation, and contact sensors, including deep and fine touch contact sensors.”

Soft somatosensory actuators. (a) After all features are printed within the second mold layer and before adding the third mold layer, (b) excess actuator matrix material is removed. (c) The anterior matrix material is added, and the contact sensor is printed. (d-f) Photographs of the SSA
removed from the mold assembly after matrix material curing. (d) Top-down and (e) end-on
views highlight the internal features of the SSAs. (f) A close-up of the contact sensor’s distal meander.

The team’s work was partially supported by the National Science Foundation through Harvard MRSEC and the Wyss Institute.

It’s been difficult in the past to integrate sensors within soft robots, mainly because sensors are rigid. But the Harvard researchers created a liquid-based, 3D printable, organic ionic conductive ink, which can actually be 3D printed inside the soft elastomer matrices that make up the majority of soft robots.

Free displacement of an SSA alternating between inflated and deflated states held for 20s. The inflation pressure is increased by 14 kPa increments to 152 kPa after each deflation to 0 kPa.

“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,” explained Wehner, now an assistant professor at UC Santa Cruz.

The team used a technique known as embedded 3D printing (EMB3D printing) to make the device. Embedded 3D printing is able to seamlessly integrate several materials and features in one soft body at a high rate of speed.

Lewis said, “This work represents the latest example of the enabling capabilities afforded by embedded 3D printing – a technique pioneered by our lab.”

The team 3D printed a soft robotic gripper, made up of three soft actuators (fingers), to see how well their sensors worked, testing the gripper’s ability to sense things like contact, curvature, inflation pressure, and temperature. Several contact sensors were embedded, so the gripper was able to sense both deep and light touches.

SSA characterization.

“The function and design flexibility of this method is unparalleled. This new ink combined with our embedded 3D printing process allows us to combine both soft sensing and actuation in one integrated soft robotic system,” said Truby.

The team’s innovative platform makes it easy to integrate sensors into soft actuating systems, which is, according to the paper, “a necessary step toward closed-loop feedback control of soft robots, machines, and haptic devices.”

Wood, also a Core Faculty Member of the Wyss Institute, explained, “Soft robotics are typically limited by conventional molding techniques that constrain geometry choices, or, in the case of commercial 3D printing, material selection that hampers design choices. The techniques developed in the Lewis Lab have the opportunity to revolutionize how robots are created — moving away from sequential processes and creating complex and monolithic robots with embedded sensors and actuators.”

Next steps for the researcher team include using machine learning to train their soft robotic grippers to grasp objects that have different temperatures, surface textures, sizes, and shapes.

 

Discuss this and other 3D printing topics at 3DPrintBoard.com or share your thoughts below. 

[Source/Images: Harvard SEAS]

 

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