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使用遗传算法对带有触觉传感器且在柔软地面上移动的蛇形机器人的中枢模式发生器网络进行参数搜索。

Parameter search of a CPG network using a genetic algorithm for a snake robot with tactile sensors moving on a soft floor.

作者信息

Tamura Hajime, Kamegawa Tetsushi

机构信息

Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University, Okayama, Japan.

出版信息

Front Robot AI. 2023 Mar 29;10:1138019. doi: 10.3389/frobt.2023.1138019. eCollection 2023.

DOI:10.3389/frobt.2023.1138019
PMID:37064573
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10090451/
Abstract

When a snake robot explores a collapsed house as a rescue robot, it needs to move through various obstacles, some of which may be made of soft materials, such as mattresses. In this study, we call mattress-like environment as a soft floor, which deforms when some force is added to it. We focused on the central pattern generator (CPG) network as a control for the snake robot to propel itself on the soft floor and constructed a CPG network that feeds back contact information between the robot and the floor. A genetic algorithm was used to determine the parameters of the CPG network suitable for the soft floor. To verify the obtained parameters, comparative simulations were conducted using the parameters obtained for the soft and hard floor, and the parameters were confirmed to be appropriate for each environment. By observing the difference in snake robot's propulsion depending on the presence or absence of the tactile sensor feedback signal, we confirmed the effectiveness of the tactile sensor considered in the parameter search.

摘要

当蛇形机器人作为救援机器人探索倒塌的房屋时，它需要穿越各种障碍物，其中一些可能由柔软材料制成，比如床垫。在本研究中，我们将类似床垫的环境称为软地板，当对其施加一定力时它会变形。我们将中央模式发生器（CPG）网络作为蛇形机器人在软地板上推进的控制方式，并构建了一个反馈机器人与地板之间接触信息的CPG网络。使用遗传算法来确定适用于软地板的CPG网络参数。为了验证所获得的参数，使用针对软地板和硬地板获得的参数进行了对比模拟，并且确认这些参数适用于每种环境。通过观察蛇形机器人根据触觉传感器反馈信号的有无在推进方面的差异，我们证实了在参数搜索中所考虑的触觉传感器的有效性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/392d/10090451/60ffb0cc4e21/frobt-10-1138019-g014.jpg
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