基于机器学习的机器人位置预测方法及其应用

R. G. Vidhya, J. Surendiran, G. Saritha
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引用次数: 4

摘要

拥有一个可以微调自身设置的机器人是跟上机械技术最新发展的绝佳方式。钟摆的原理是这个观点的基础。一个框架将经历一个自我调整的周期,从内到外支撑自己。本研究的目的是为机器人提供自我调节和平衡的手段,使其有可能成功地解决与维持摇摇欲坠的结构相关的困难。通过分析加速度计和旋转器的数据,可以计算出机器人的精确三维位置并发送给控制器。然后,监管机构自己的代码合法地指导驱动模块的轮子旋转,提高机器人的稳定性。与四个轮子的机器人相比,这个机器人的优势在于它能够快速旋转并避开障碍物。正因为如此,它已成为一些现代语境中不可或缺的资源。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Machine Learning Based Approach to Predict the Position of Robot and its Application
Having a robot that can fine-tune its own settings is a terrific way to keep up with the latest developments in mechanical technology. The principle of the pendulum serves as the basis for this idea. A framework will go through a cycle of self-adjustment to bolster itself from the inside out. The goal of this study is to provide the robot with the means of self-adjustment and balance, making it possible for it to successfully address the difficulties associated with maintaining a shaky structure. By analyzing data from the accelerometer and gyrator, the robot's accurate three-dimensional location may be calculated and sent to a controller. The regulator's own code then legitimately directs the drive module's wheels to revolve, improving the robot's steadiness. When compared to robots with four wheels, this one's superiority lies in its ability to swiftly spin and avoid obstructions. Because of this, it has become an indispensable resource in several modern contexts.
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