PennState Researchers Develop Flexible Magnetic Semiautonomous Robot

R&D Breakthrough Robots and Cobots

An international research team led by PennState has successfully developed a small, semiautonomous flexible robot that may one day help locate victims in disaster zones or deliver medicine inside the human body.

The work, which also included support from The National Research Foundation of South Korea and the Korea Institute of Science and Technology, integrates sensors and flexible electronics with magnetically controlled soft robotics, as recently detailed in Nano-Micro Letters.    supported this research.

The soft robot developed at PennState can bend, crawl, and roll in response to magnetic fields, enabling applications in rescue missions and minimally invasive medicine. These tiny robots use magnetism to move and explore tight spaces, potentially including disaster rubble or the human body. (Image Courtesy of Penn State; Jennifer M. McCann)

The soft robots are constructed from flexible materials capable of mimicking the biological movements of living organisms. Their material of construction makes them especially well-suited for navigating space-constrained environments, such as under rubble or debris. However, embedding sensors and electronics in these robots has traditionally proven difficult. According to Huanyu “Larry” Cheng, James L. Henderson, Jr. Memorial Associate Professor of Engineering Science and Mechanics at PennState and co-corresponding author of the study, the main challenge was enabling bidirectional interaction between the robot and its surroundings.

“The biggest challenge really was to make it smart,” Cheng said. “For most applications, soft robotics have been a one-way communication system, meaning they rely on external control to navigate through complex environments. Our goal was to integrate smart sensors so these robots could interact with their surroundings and operate with minimal human intervention.”

“We wanted to design a system where soft robotics and flexible electronics work together seamlessly,” Cheng said. “Traditional electronics are rigid, which makes integration difficult. Our solution was to distribute the electronic components in a way that preserves the robot’s flexibility while maintaining robust performance.”

Cheng and his team shot videos of the robots in action, capturing their dynamic behavior as they crawl and roll into a ball to move along a simple course. The robots move using hard magnetic materials embedded in their flexible structure, which allows the robots to respond predictably to an external magnetic field stimuli. By adjusting the field’s strength and direction, researchers found that they could control robotic movements, such as bending, twisting, or crawling, without the need for onboard power or physical connections such as wires.

A major technology development hurdle, however, was figuring out how to keep the flexible electronics from hindering robotic movement.

“Even though we designed the electronics to be flexible, their stiffness is still hundreds to thousands of times greater than the soft robotic material,” Cheng said. “To overcome this, we distributed the electronics across the structure, reducing their impact on movement.”

Another challenge was blocking unwanted electrical interference, which can disrupt electronic device or system functionality. Interference comes from outside sources, like other electronics or wireless signals, can hinder movement and affect sensor performance.

“Magnetic fields are crucial for controlling motion, but they can also disrupt electronic signals,” Cheng noted. “We had to carefully design the electronic layout to minimize these interactions, ensuring that the sensors remained functional even in the presence of strong magnetic fields.”

With the minimization of magnetic interference, researchers found that the robots can be guided remotely using electromagnetic fields or handheld magnets — which limits the amount of manual human intervention they require. Additionally, integrated sensors allow them to react autonomously to environmental cues. In search-and-rescue, for example, the robots are smart enough to navigate debris by detecting heat or obstacles. In medical applications, they might respond to pH changes or pressure, ensuring precise drug delivery or accurate sample collection.

The next step for Cheng’s team is to refine the technology for such applications — including creating a “robot pill.”

“One of the most fascinating potential applications is in implantable medical devices,” said co-author Suk-Won Hwang, associate professor at the Graduate School of Converging Science and Technology, Korea University. “We’re working on miniaturizing the system to make it suitable for biomedical use. Imagine a small robotic system that could be swallowed like a pill, navigate through the gastrointestinal tract and detect diseases or deliver drugs precisely where they’re needed.”

Such technology could provide a less invasive alternative to traditional medical diagnostic procedures, like biopsies, gathering data directly from the patient in real time, according to the researchers.

“With integrated sensors, these robots could measure pH levels, detect abnormalities and even deliver medication to precise locations inside the body,” Cheng explained. “That means fewer invasive surgeries and more targeted treatments, improving patient outcomes.”

Cheng said he also envisions future applications in vascular treatments.

“If we can make these robots even smaller, they could be injected into blood vessels to treat cardiovascular diseases or deliver medication directly to affected areas,” Cheng said. “That would open up entirely new possibilities for non-invasive medical treatments.”

Along with Cheng and Hwang, other authors of the study from PennState include Bowen Li, research assistant in engineering science and mechanics, and Ankan Dutta, doctoral student in mechanical engineering who is also affiliated with the Center for Neural Engineering. Joong Hoon Lee, Gwan-Jin Ko, Tae-Min Jang, Won Bae Han, Sueng Min Yang, Dong-Je Kim, Heeseok Kang, Jun Hyeon Lim, Chan-Hwi Eom and So Jeong Choi, KU-KIST Graduate School of Converging Science and Technology, Korea University; and Sungkeun Han, Semiconductor R&D Center, Samsung Electronics Co., also contributed to the paper.

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Source: PennState


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