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首页> 外文期刊>Robotics, IEEE Transactions on >Two-Dimensional Autonomous Microparticle Manipulation Strategies for Magnetic Microrobots in Fluidic Environments
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Two-Dimensional Autonomous Microparticle Manipulation Strategies for Magnetic Microrobots in Fluidic Environments

机译:流体环境中电磁微型机器人的二维自主微粒操纵策略

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摘要

This study develops autonomous manipulation strategies for a mobile untethered microrobot that operates on a 2-D surface in a fluidic environment. The microrobot, which is a permanent magnet, is under m in all dimensions and is actuated by oscillating external magnetic fields. Two types of manipulations are considered: 1) front pushing, where the microrobot pushes a micro-object by direct contact; and 2) side pushing, which can result in noncontact pushing, where the fluid flow fields that are generated by a translating microrobot are used to displace a micro-object. Physical models are provided to estimate the displacement of the micro-object due to the fluid motion. Model-based controllers to perform contact and noncontact manipulation are proposed, which iteratively correct emerging manipulation behaviors to improve performance. It is found that using a model-based solution as a feed-forward input, which is combined with a learning controller, can significantly improve micro-object pushing performance. Finally, we begin to address the problem to assemble two micro-objects together using the microrobot, which is only successful by using a side-pushing method.
机译:这项研究为在流体环境中在二维表面上运行的移动式无限制微型机器人开发了自主操纵策略。微型机器人是永久磁铁,其所有尺寸均小于m,并且通过振荡外部磁场来致动。考虑了两种类型的操纵:1)前推,微型机器人通过直接接触推动微物体; 2)侧面推动,这可能会导致非接触推动,在这种情况下,由平移微型机器人产生的流体流场用于移动微型物体。提供物理模型以估计由于流体运动而引起的微对象的位移。提出了用于执行接触和非接触操纵的基于模型的控制器,该控制器可迭代地纠正出现的操纵行为以提高性能。发现将基于模型的解决方案用作前馈输入(与学习控制器结合使用)可以显着提高微对象推入性能。最后,我们开始解决使用微型机器人将两个微型对象组装在一起的问题,只有通过使用侧推方法才能成功。

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