SerpenBot, a Laser Driven Locomotive Microrobot for Dry Environments using Learning Control

Zhong Yang, Moath H. A. Alqatamin, A. Sherehiy, Ruoshi Zhang, Mojtaba Al Hudibi, N. Taghavi, D. Popa
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引用次数: 1

Abstract

In this paper, we introduce the Serpenbot, a microrobot smaller than 1mm in size that is powered via laser energy and operates in dry environments. The microrobot achieves locomotion on a Si substrate by selective coupling of laser energy between its two legs. The coupling mechanism is achieved by laser beam selective irradiation of the microrobot’s body to initiate the gait. Multi-Physics Models developed in our past work are difficult to use in formulating a microrobot controller. Therefore, in this paper, the microrobot model is simplified to differential drive kinematics that approximates the robot behavior, and the model was used to formulate a neural-network learning controller that can steer the robot to desired locations on the silicon substrate. Simulations predict the robot position regulation achieved by learning of the inverse robot Jacobian. Preliminary experimental results are also presented to confirm that this steering controller will also work in practice.
基于学习控制的干燥环境激光驱动机车微型机器人SerpenBot
在本文中,我们介绍了Serpenbot,一种尺寸小于1mm的微型机器人,通过激光能量供电,在干燥环境中工作。该微型机器人通过其两条腿之间的激光能量选择性耦合在硅衬底上实现运动。耦合机制是通过激光束选择性照射微型机器人的身体来启动步态。在我们过去的工作中开发的多物理场模型很难用于制定微型机器人控制器。因此,本文将微型机器人模型简化为近似机器人行为的微分驱动运动学,并利用该模型构建神经网络学习控制器,使机器人在硅衬底上到达期望的位置。仿真预测了通过学习机器人逆雅可比矩阵实现的机器人位置调节。初步的实验结果也证实了该转向控制器在实际应用中是可行的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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