Shi Xinpeng, Li Yongge, Suleiman Kheder
School of Mathematics and Statistics, Northwestern Polytectnical University, Xi'an 710072, China.
Research and Development Institute of Northwestern Polytectnical University in Shenzhen, Shenzhen 518063, China.
Micromachines (Basel). 2025 Mar 25;16(4):373. doi: 10.3390/mi16040373.
This study investigates the complex dynamic behavior of three-tailed helical microrobots operating in confined spaces. A stochastic dynamic model has been developed to analyze the effects of input angular velocity, current, fluid viscosity, and channel width on their motion trajectories, velocity, mean squared displacement (MSD), and wobbling rate. The results indicate that Gaussian white noise exerts a dispersive driving effect on the motion characteristics of the microrobots, leading to a 49% reduction in their velocity compared to deterministic conditions. Additionally, the time required for microrobots to traverse from the initial position to the bifurcation point decreases by 65% when the current is increased and by 39% when the fluid viscosity is reduced. These findings underscore the importance of optimizing control parameters to effectively mitigate noise impacts, enhancing the practical performance of the microrobots in real-world applications. This research offers solid theoretical support and guidance for the deployment of microrobots in complex environments.
本研究调查了在受限空间中运行的三尾螺旋微型机器人的复杂动态行为。已开发出一个随机动力学模型,以分析输入角速度、电流、流体粘度和通道宽度对其运动轨迹、速度、均方位移(MSD)和摆动率的影响。结果表明,高斯白噪声对微型机器人的运动特性产生分散驱动效应,导致其速度与确定性条件相比降低了49%。此外,当电流增加时,微型机器人从初始位置穿越到分叉点所需的时间减少65%,当流体粘度降低时减少39%。这些发现强调了优化控制参数以有效减轻噪声影响的重要性,增强微型机器人在实际应用中的实际性能。本研究为微型机器人在复杂环境中的部署提供了坚实的理论支持和指导。