Summary: Researchers have designed a “mindless” soft robot that can autonomously navigate complex environments using physical intelligence.
Unlike their previous model, which could only walk on obstacles, this robot can walk on its own. This unique movement is due to an asymmetrical design with one half exerting more force on the ground.
As a result, it can move in arcs, move through dynamic mazes, and avoid getting stuck in parallel objects.
Key Facts:
- A soft robot operates through “physical intelligence,” meaning its behavior is determined by its structural design and materials, eliminating the need for computer or human guidance.
- The robot is made of ribbon-like liquid crystal elastomers and sets into motion when placed on a surface hotter than the surrounding air; The hotter the surface, the faster it will roll.
- The robot’s asymmetric design enables it to move in arcs, allowing it to navigate mazes without getting stuck, and also maneuver its way out of parallel obstacles.
Source: State of North Carolina
Researchers who created a soft robot that can navigate a simple maze without human or computer direction have now built on that work, creating a “mindless” soft robot that can navigate more complex and dynamic environments.
“In our previous work, we showed that our soft robot is able to turn and turn around a very simple obstacle course,” says Ji Yin, co-corresponding author of a paper on the work and associate professor of mechanical and aerospace. Engineering at North Carolina State University.
“However, he could not turn without encountering an obstacle. In practical terms this means that the robot can sometimes get stuck, bouncing back and forth between parallel obstacles.
“We have developed a new soft robot that is able to turn on itself, navigate a winding maze, even negotiate around obstacles. And it’s all done using physical intelligence rather than computer guidance.”
Physical intelligence refers to dynamic objects – such as soft robots – whose behavior is controlled by their structural design and the materials they are made of without being directed by computers or human intervention.
Like the previous version, the new soft robot is made of ribbon-like liquid crystal elastomers. When the robot is placed on a surface that is at least 55 degrees Celsius (131 degrees Fahrenheit), which is hotter than the surrounding air, the part of the ribbon touching the surface contracts, while the part of the ribbon exposed to air. No it induces a rolling motion; The warmer the surface, the faster the robot will roll.
However, while the design of the previous version of the soft robot was symmetrical, the new robot has two distinct parts. One half of the robot is like a winding ribbon that stretches out in a straight line, while the other half is like a tighter winding ribbon that winds around itself like a spiral staircase.
This asymmetrical design means that one end of the robot exerts more force on the ground than the other. Think of a plastic cup with a mouth wider than its base. If you spin it on the table, it doesn’t spin in a straight line – it makes an arc as it spins on the table. This is due to its asymmetrical shape.
“The concept behind our new robot is very simple: because of its asymmetric structure, it turns without coming into contact with an object,” says Yao Zhao, first author of the paper and a postdoctoral researcher at NC State.
“So, while he’s still changing direction does Coming into contact with an object – allows it to navigate the maze – it cannot get stuck in parallel objects. Instead, his ability to move in arcs allows him to move essentially freely.
The researchers demonstrated the asymmetric soft robot design’s ability to navigate more complex mazes—including mazes with moving walls—and fit into a space smaller than its body size. The researchers tested the new robot design on metal surfaces and sand.
“This work is another step in helping us develop innovative approaches to soft robot design – especially for applications where soft robots can extract heat energy from their environment,” says Yin.
The paper, “Physiologically Intelligent Autonomous Soft Robotic Maze Escaper,” will be published in the journal Sept. 8. Science advances. The paper’s first author is Yao Zhao, a postdoctoral researcher at NC State.
Hao Su, associate professor of mechanical and aerospace engineering at NC State, is a co-corresponding author. Additional co-authors include recent Ph.D. including Yaoye Hong. Graduate of NC State; Yanbin Li, a postdoctoral researcher at NC State; and Fangjie Qi and Haitao Qing, both Ph.D. Students from NC State.
Funding: This work was supported by the National Science Foundation under grants 2005374, 2126072, 1944655, and 2026622.
About this robotics and neurotech research news
Author: Matt Shipman
Source: State of North Carolina
Contact: Matt Shipman – North Carolina State
Image: Image is credited to Neuroscience News
Original Research: Free access.
“Physically Intelligent Autonomous Soft Robotic Maze Escaper” by Ji Yin et al. Science advances
Abstract
Physiologically Intelligent Autonomous Soft Robotic Maze Escape
Autonomous maze navigation is attractive but challenging in soft robotics for exploring previously unknown unstructured environments, as it often requires a human-like brain integrating controls for onboard power, sensors, and computational intelligence.
Here, we harness both geometric and material intelligence in liquid crystal elastomer-based self-rolling robots for autonomous exit through complex multichannel mazes without the need for a human-like brain.
The soft robot powered by environmental thermal energy has an asymmetric geometry with hybrid twisted and helical shapes at the two ends. Such geometric asymmetry enables inherent active and continuous self-twisting capability, unlike its symmetric counterparts in either twisted or helical shapes that exhibit momentary self-twisting only through untwisting.
Combining self-snapping with motion reflection, it features a unique curved zigzag path to avoid getting stuck in its counterparts, allowing it to successfully self-extricate itself from a variety of challenging mazes, including mazes on granular terrain, mazes with narrow gaps, and even mazes with in-situ. Changing the layout.