Brainless robot navigates mazes – Neuroscience news

Summary: Researchers have designed a “brainless” soft robot that can autonomously navigate complex environments using physical intelligence.

Unlike their previous model, which could only turn on when encountering obstacles, this robot can turn on its own. This unique movement is due to the asymmetrical design with one half exerting more force on the ground.

Therefore, it can move in arcs, go through dynamic mazes, and avoid getting stuck between parallel objects.

Major Events:

1. The soft robot operates through “physical intelligence,” meaning its behavior is determined by structural design and materials, eliminating the need for computer or human guidance.
2. The robot is made of ribbon-like liquid crystal elastomer and moves when placed on a surface that is hotter than the surrounding air; The warmer the surface, the faster it rolls.
3. The robot’s asymmetrical design allows it to move in an arc, helping it move through the maze without getting stuck and even wiggle its way out between parallel obstacles.

Source: North Carolina State

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 ” can navigate more complex and dynamic environments.

“In previous research, we demonstrated that our soft robot can Turning and turning to get around an obstacle is simple.” engineering at North Carolina State University.

“However, it cannot turn around unless it encounters 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 rotates on its own, allowing it to navigate zigzag mazes and even move around obstacles. And it’s all done using physical intelligence, rather than being guided by a computer.”

Physical intelligence refers to dynamic objects – such as soft robots – whose behavior is governed by the structural design and materials from which they are made, rather than controlled by computers or human intervention.

Like the previous version, the new soft robot is made of ribbon-like liquid crystal elastomer. When the robot is placed on a surface with a temperature of at least 55 degrees Celsius (131 degrees F), hotter than the surrounding air, the part of the ribbon that is in contact with the surface will contract, while the part of the ribbon that is in contact with the air will shrink. The gas will contract. Are not. This causes a rolling motion; The warmer the surface, the faster the robot rolls.

However, while the previous version of the soft robot had a symmetrical design, the new robot has two distinct halves. One half of the robot is shaped like a twisted ribbon that stretches in a straight line, while the other half is shaped like a tighter twisted ribbon that also twists 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 the bottom. If you roll it across the table, it won’t roll in a straight line – it forms an arc as it moves across the table. That’s because of its asymmetrical shape.

“The concept behind our new robot is quite simple: thanks to its asymmetric design, it rotates without need to come into contact with the object.

“So while it still changes direction when it do contact with an object – allows it to navigate the maze – it cannot get stuck between parallel objects. Instead, its ability to move in an arc essentially allows it to wiggle freely.”

Researchers have demonstrated the ability of the asymmetric soft robot design to navigate more complex mazes – including mazes with moving walls – and fit into spaces narrower than body size its. The researchers tested the new robot design on both metal surfaces and sand.

“This work is another step forward in helping us develop innovative approaches to soft robot design – especially for applications where soft robots can harvest thermal energy,” said Yin. from their environment”.

The article “Physically Intelligent Autonomous Soft Robot Maze Escaper” will be published in the journal on September 8 Scientific advance. 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. Other co-authors include Yaoye Hong, a recent Ph.D. graduated from NC State; Yanbin Li, postdoctoral researcher at NC State; and Fangjie Qi and Haitao Qing, both with Ph.D. student at NC State.

Expense: The work was performed with support from the National Science Foundation under grants 2005374, 2126072, 1944655, and 2026622.

About this research news about robotics and neurotechnology

Author: Matt Shipman
Source: North Carolina State
Contact: Matt Shipman – North Carolina State
Image: Image credited to Neuroscience News

Original research: Open access.
“Physically intelligent autonomous soft robot maze escaper” by Jie Yin et al. Scientific advance

abstract

Escape from the maze of physically intelligent autonomous soft robots

Automated maze navigation is appealing but also challenging for soft robots to explore unknown unstructured environments, as it often requires a human-like brain that integrates power, sensors and on-board computational intelligence control capabilities.

Here, we report the exploitation of both geometric and material intelligence in a self-rolling robot based on liquid crystal elastomers to autonomously escape complex multichannel mazes without the need for a human-like brain. People.

The soft robot powered by environmental thermal energy has an asymmetrical shape with a hybrid twisted and twisted shape at both ends. Such geometric asymmetry allows for integrated active and sustained rotation, unlike its symmetric counterparts in helices or spirals which only exhibit transient rotation through no twist.

Incorporating a selfie feature to mirror movement, it displays unique curved zigzag lines to avoid getting stuck in its counterparts, allowing for successful self-escape from a variety of challenging mazes, including mazes on granular terrain, mazes with narrow gaps, and even mazes where the layout changes.