No-brainer: Morphological Computation driven Adaptive Behavior in Soft Robots

Fuente: arXiv
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Autores principales: Mertan, Alican, Cheney, Nick
Formato: Preprint
Publicado: 2024
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author Mertan, Alican
Cheney, Nick
author_facet Mertan, Alican
Cheney, Nick
contents It is prevalent in contemporary AI and robotics to separately postulate a brain modeled by neural networks and employ it to learn intelligent and adaptive behavior. While this method has worked very well for many types of tasks, it isn't the only type of intelligence that exists in nature. In this work, we study the ways in which intelligent behavior can be created without a separate and explicit brain for robot control, but rather solely as a result of the computation occurring within the physical body of a robot. Specifically, we show that adaptive and complex behavior can be created in voxel-based virtual soft robots by using simple reactive materials that actively change the shape of the robot, and thus its behavior, under different environmental cues. We demonstrate a proof of concept for the idea of closed-loop morphological computation, and show that in our implementation, it enables behavior mimicking logic gates, enabling us to demonstrate how such behaviors may be combined to build up more complex collective behaviors.
format Preprint
id arxiv_https___arxiv_org_abs_2407_16613
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle No-brainer: Morphological Computation driven Adaptive Behavior in Soft Robots
Mertan, Alican
Cheney, Nick
Robotics
Artificial Intelligence
Neural and Evolutionary Computing
It is prevalent in contemporary AI and robotics to separately postulate a brain modeled by neural networks and employ it to learn intelligent and adaptive behavior. While this method has worked very well for many types of tasks, it isn't the only type of intelligence that exists in nature. In this work, we study the ways in which intelligent behavior can be created without a separate and explicit brain for robot control, but rather solely as a result of the computation occurring within the physical body of a robot. Specifically, we show that adaptive and complex behavior can be created in voxel-based virtual soft robots by using simple reactive materials that actively change the shape of the robot, and thus its behavior, under different environmental cues. We demonstrate a proof of concept for the idea of closed-loop morphological computation, and show that in our implementation, it enables behavior mimicking logic gates, enabling us to demonstrate how such behaviors may be combined to build up more complex collective behaviors.
title No-brainer: Morphological Computation driven Adaptive Behavior in Soft Robots
topic Robotics
Artificial Intelligence
Neural and Evolutionary Computing
url https://arxiv.org/abs/2407.16613