Cheetahs inspire robots that can move faster, grasp more precisely

Cheetahs inspire robots that can move faster, grasp more precisely

adminMay 10, 20207min170
adminMay 10, 20207min170
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Soft robots are typically slower and are less precise for manipulation than more rigid devices, but biomechanics have inspired advances in those capabilities. Researchers at North Carolina State University have developed soft robots inspired by cheetahs. With two states of a flexible spine, the new type of robot can move faster on solid surfaces or […]


Soft robots are typically slower and are less precise for manipulation than more rigid devices, but biomechanics have inspired advances in those capabilities. Researchers at North Carolina State University have developed soft robots inspired by cheetahs.

With two states of a flexible spine, the new type of robot can move faster on solid surfaces or in the water than previous soft robots. They are also capable of grabbing objects delicately or with sufficient strength to lift heavy objects.

“Cheetahs are the fastest creatures on land, and they derive their speed and power from the flexing of their spines,” stated Jie Yin, an assistant professor of mechanical and aerospace engineering at North Carolina State University and corresponding author of a paper on the new soft robots.

“We were inspired by the cheetah to create a type of soft robot that has a spring-powered, ‘bistable’ spine, meaning that the robot has two stable states,” he said. “We can switch between these stable states rapidly by pumping air into channels that line the soft, silicone robot. Switching between the two states releases a significant amount of energy, allowing the robot to quickly exert force against the ground. This enables the robot to gallop across the surface, meaning that its feet leave the ground.”

“Previous soft robots were crawlers, remaining in contact with the ground at all times,” Yin noted. “This limits their speed.”

Soft robots to LEAP like cheetahs

The fastest soft robots until now could move at speeds of up to 0.8 body lengths per second on flat, solid surfaces. The new class of soft robots, which are called “Leveraging Elastic instabilities for Amplified Performance” (LEAP), are able to reach speeds of up to 2.7 body lengths per second — more than three times faster — at a low actuation frequency of about 3Hz. These new robots are also capable of running up steep inclines, which can be challenging or impossible for soft robots that exert less force against the ground.

These “galloping” LEAP robots are approximately 7 cm (2.7 in.) long and weigh about 45 g (1.58 oz.).

Researchers have developed new soft robots inspired by cheetahs. Source: Jie Yin, NC State University

The researchers also demonstrated that the LEAP design could improve swimming speeds for soft robots. Attaching a fin, rather than feet, a LEAP robot was able to swim at a speed of 0.78 body lengths per second, in comparison with 0.7 body lengths per second for the previous fastest swimming soft robot.

“We also demonstrated the use of several soft robots working together, like pincers, to grab objects,” Yin said. “By tuning the force exerted by the robots, we were able to lift objects as delicate as an egg, as well as objects weighing 10 kilograms or more.”

The researchers note that this work serves as a proof of concept, and are optimistic that they can modify the design to make LEAP robots that are even faster and more powerful.

“Potential applications include search and rescue technologies, where speed is essential, and industrial manufacturing robotics,” Yin says. “For example, imagine production line robotics that are faster, but still capable of handling fragile objects.

“We’re open to collaborating with the private sector to fine-tune ways they can incorporate this technology into their operations,” he said.

The paper, “Leveraging Elastic instabilities for Amplified Performance (LEAP): spine-inspired high-speed and high-force soft robots,” was published in the journal Science Advances. The first author of the paper is Yichao Tang, a former Ph.D. student of Jie Yin’s when Yin was on faculty at Temple University. The paper was co-authored by Yinding Chi, a Ph.D. student at NC State; Omid Maghsoudi and Andrew Spence of Temple; Jiefeng Sun and Jianguo Zhao of Colorado State University; and Tzu-Hao Huang and Hao Su of the City University of New York.

The work was done with support from the National Science Foundation under Grants 2010717 and 2005374.



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