Brainless robots navigate mazes Neuroscience News
summary: Researchers have designed a soft, “brainless” robot that can autonomously navigate through complex environments using bodily intelligence.
Unlike the previous model, which can only run when encountering obstacles, this robot can transform on its own. This unique movement is due to the asymmetrical design where the half exerts more force on the ground.
Thus, they can move in arcs, traverse dynamic mazes, and avoid getting caught between parallel objects.
- The soft robot operates through “body intelligence,” meaning its behavior is dictated by its structural design and materials, eliminating the need for computer or human guidance.
- This robot is made of ribbon-like liquid crystal elastomers and moves when placed on a surface hotter than the surrounding air; The warmer the surface, the faster it will spin.
- The robot’s asymmetrical design enables it to move in arcs, allowing it to navigate mazes without getting stuck, and even move between parallel obstacles.
source: North Carolina
Researchers who created a soft robot that can navigate simple mazes without human or computer guidance have now built on that work, creating a “brainless” soft robot that can navigate more complex and dynamic environments.
“In our previous work, we demonstrated that our soft robot was able to warp and turn through a very simple obstacle course,” says Ji Yin, co-author of a paper on the work and associate professor of mechanical and aerospace engineering. Engineering at North Carolina State University.
However, he was only able to transform if he encountered an obstacle. In practical terms, this meant that the robot could sometimes get stuck, jumping back and forth between parallel obstacles.
“We have developed a new soft robot that is able to spin on its own, allowing it to make its way through twisty mazes, and even overcome moving obstacles. It is all done using physical intelligence, rather than being guided by a computer.
Bodily intelligence refers to dynamic objects, such as soft robots, whose behavior is governed by their structural design and materials, rather than being directed by a computer or human intervention.
As with the previous version, the new soft robots are made of ribbon-like liquid crystal elastomers. When the robots are placed on a surface that is at least 55°C (131°F), which is hotter than the surrounding air, the part of the tape that is in contact with the surface contracts, while the part of the tape that is exposed to the air does not. This results in a rolling motion. The warmer the surface, the faster the robot will spin.
However, while the previous version of the soft robot had a symmetrical design, the new robot has two distinct halves. Half of the robot is a twisting bar that runs in a straight line, while the other half is a tighter twisting bar that also loops 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 that has a mouth wider than its base. If you roll it across the table, it doesn’t roll in a straight line – it just makes an arc as it goes across the table. This is due to its asymmetrical shape.
“The concept behind the new robot is fairly simple: Because of its asymmetrical design, it spins without you having to touch anything,” says Yao Zhao, first author of the paper and a postdoctoral researcher at NC State.
So, while still changing directions when he does Do You come into contact with an object – allowing it to navigate mazes – and it cannot get stuck between parallel objects. Instead, its ability to move in arcs allows it to wiggle its way around freely.
The researchers demonstrated the ability of the soft, asymmetrical robot design to navigate more complex mazes – including mazes with moving walls – and fit into spaces smaller than its body size. The researchers tested the new robot design on a metal surface and in sand.
“This work is another step forward in helping us develop innovative approaches to designing soft robots—particularly for applications where soft robots will be able to harvest heat energy from their environment,” says Yin.
The paper, “Body Intelligence Soft Robotic Labyrinth Escape,” will be published September 8 in the journal. 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-author. Additional co-authors include Yaoye Hong, a recent Ph.D. North Carolina State graduate. Yanbin Li, a postdoctoral researcher at NC State; and Fangjie Qi and Haitao Qing, both Ph.D. students in NC State.
Funding: The work was completed with support from the National Science Foundation under grants 2005374, 2126072, 1944655 and 2026622.
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author: Matt Shipman
source: North Carolina
communication: Matt Shipman – North Carolina State
picture: Image credited to Neuroscience News
Original search: open access.
“Body Intelligence Soft Robotic Labyrinth Escape” by Ji Yin et al. Science advances
Physically intelligent soft robotic maze escape
Autonomous navigation of a maze is attractive yet challenging in the field of soft robotics to explore previously unknown unstructured environments, often requiring a human-like mind integrating onboard power, sensors and control for computational intelligence.
Here, we report harnessing both engineering and material intelligence in self-rolling robots based on liquid elastomer for autonomous escape from complex, multi-channel mazes without the need for a human-like brain.
The soft robot powered by ecothermal energy features an asymmetrical geometry with hybrid twisting and spiral shapes on two ends. This geometric asymmetry enables active and sustained self-rotation capabilities, in contrast to their symmetric counterparts in torsion or helical shapes that only exhibit transient self-rotation through torsion unwinding.
Combined with self-capture of motion reflexes, it shows unique curving zigzag paths to avoid being trapped by its counterparts, allowing successful self-escape from various challenging mazes, including mazes on granular terrain, mazes with narrow gaps, and even mazes on location changing layouts .