The robot's segments can flatten and extend into cylinders. (Image: Frank Wojciechowski)
Soft robots can be challenging to guide because steering equipment often increases the robot’s rigidity and cuts its flexibility. The new design overcomes those problems by building the steering system directly into the robot’s body, said Tuo Zhao, a postdoctoral researcher at Princeton.
In an article published May 6 in the journal PNAS, the researchers describe how they created the robot out of modular, cylindrical segments. The segments, which can operate independently or join to form a longer unit, all contribute to the robot’s ability to move and steer. The new system allows the flexible robot to crawl forward and reverse, pick up cargo and assemble into longer formations.
“The concept of modular soft robots can provide insight into future soft robots that can grow, repair, and develop new functions,” the authors said in their article.
Zhao said the robot’s ability to assemble and split up on the move allows the system to work as a single robot or a swarm.
“Each segment can be an individual unit, and they can communicate with each other and assemble on command,” he said. “They can separate easily, and we use magnets to connect them.”
Zhao works in Glaucio Paulino’s lab in the Department of Civil and Environmental Engineering and the Princeton Materials Institute. Paulino, the Margareta Engman Augustine Professor of Engineering, has created a body of research that applies origami to a wide array of engineering applications from medical devices to aerospace and construction.
“We have created a bio-inspired plug-and-play soft modular origami robot enabled by electrothermal actuation with highly bendable and adaptable heaters,” Paulino said. “This is a very promising technology with potential translation to robots that can grow, heal, and adapt on demand.”
In this case, the researchers began by building their robot out of cylindrical segments featuring an origami form called a Kresling pattern. The pattern allows each segment to twist into a flattened disk and expand back into a cylinder. This twisting, expanding motion is the basis for the robot’s ability to crawl and change direction. By partially folding a section of the cylinder, the researchers can introduce a lateral bend in a robot segment. By combining small bends, the robot changes direction as it moves forward.
One of the most challenging aspects of the work involved developing a mechanism to control the bending and folding motions used to drive and steer the robot. Researchers at North Carolina State University developed the solution. They used two materials that shrink or expand differently when heated (liquid crystal elastomer and polyimide) and combined them into thin strips along the creases of the Kresling pattern. The researchers also installed a thin stretchable heater made of silver nanowire network along each fold. Electrical current on the nanowire heater heats the control strips, and the two materials’ different expansion introduces a fold in the strip. By calibrating the current, and the material used in the control strips, the researchers can precisely control the folding and bending to drive the robot’s movement and steering.
“Silver nanowire is an excellent material to fabricate stretchable conductors. Stretchable conductors are building blocks for a variety of stretchable electronic devices including stretchable heaters. Here we used the stretchable heater as the actuation mechanism for the bending and folding motions” said Lead Researcher and Professor Yong Zhu.
Tuo Zhao, a postdoctoral researcher, with origami patterns used in robotics research. (Image: Frank Wojciechowski)
Shuang Wu, a postdoctoral researcher in Zhu’s lab, said the lab’s previous work used the stretchable heater for continuously bending a bilayer structure. “In this work we achieved localized, sharp folding to actuate the origami pattern. This effective actuation method can be generally applied to origami structures (with creases) for soft robotics,” Wu said.
The researchers said that the current version of the robot has limited speed, and they are working to increase the locomotion in later generations.
Zhao said the researchers also plan to experiment with different shapes, patterns, and instability to improve both the speed and the steering.
Here is an exclusive Tech Briefs interview with Zhao, edited for length and clarity.
Tech Briefs: What was the biggest technical challenge you faced while developing this soft robot?
Zhao: The biggest challenge was to enable multiple functions. For example, in terms of locomotion, most robots can only move in one direction. However, we’re able to do bidirectional locomotion, which means that by programming the sequence of the sharp folding we can enable it to move in different directions.
Another challenge regarding locomotion is the theory. With this robot we can not only do bidirectional locomotion, but we can also make the robot turn. Also, another functionality our robot has is cargo pick-up. We need an improved concept regarding use of this model.
Tech Briefs: What are your next steps?
Zhao: In the next step, we’re thinking about investigating different types of geometry to make the locomotion more robust. In the paper, we mentioned that the limitation of this present work is the speed, which is below the average robot’s. So, we’re thinking about different ways to increase the speed.
For example, there is a concept — mechanical instability — in terms of geometry. Instability means this thing can snap. We are modifying the geometry to integrate this mechanical instability into the geometry. With that, we can potentially increase the speed of the robot.
Another challenge we have is that in the present work, we did an open-loop control for the locomotion, to control how it moves. We now want to embed some sensing capability into the robot, such that, for example, when it hits a wall, it can navigate itself to avoid it. So, those are the things we are thinking to integrate into the robot to make the locomotion more robust.
Tech Briefs: The article I read says, “The researchers said that the current version of the robot has limited speed and they're working to increase the locomotion in later generations.” How is that coming along? Do you have any updates you can share?
Zhao: Right now, we are in the theoretical stage. So, we have a simulation tool to, for example, test our modification of the geometry. The simulation showed that we did, in fact, increase the locomotion speed about 40 percent. Now we are in the process of making those changes in the lab to verify our theory to see if this really works.
Tech Briefs: Do you have any set plans for further research?
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Zhao: First, we are trying to modify the design to see if we can increase the speed. And we want to implement some sensors on the robot. The challenge is that the sensor has to be flexible, because we have a soft robot whose body can undergo tremendous deformation — there is local bending of the panels. We plan to use some flexible PCBs to integrate flexible electronics, which may enable sensing capability for the robot.
Tech Briefs: To what kind of applications could this be applied?
Zhao: With this robot, we are thinking, potentially, it could travel in a confined space. For example, in disaster rescue, after an earthquake — it could be very complex, destroyed buildings, rubble, etc. — a standard robot might not work. This type of soft robot could play a big role because it’s small and can travel in a confined space, for example, maybe a space between rocks and the fallen concrete.
Then, we are thinking this could be a multiple-robot concept. For example, if we have multiple types of this robot, we can put all of them on the site and then they can try to find survivors. And because of their capability, maybe we can deliver some basic medicine — some water to give the survivors, some basic needs for when the robot reaches them. Then, hopefully, if the robots can communicate, they can report as to where the survivors are and seek assistance. So, that’s one potential application we have in mind.
Topics:
Automation Design Mechanical Components Robotics
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