Magnetic Localization Technology of Capsule Robot Based on Magnetic Sensor Array

Fu, Qiang; Wang, Xinrui; Guo, Jian; Guo, Shuxiang; Cai, Zhuocong

doi:10.1109/icma49215.2020.9233664

Cited by 5 publications

(2 citation statements)

References 8 publications

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“…The capsule robot consists of modules with a polyethene shell and an O-ring magnet. When swallowing a multimodule capsule robot, based on the previous research on the motion characteristics of a multimodule capsule robot, the difference of starting and cut-off frequency of each module can be used to realize its separation or whole movement [26][27][28]. The parameters of capsule robots A, B, and C are used in this paper (Table 1).…”

Section: System Configurationmentioning

confidence: 99%

A Magnetically Capsule Robot for Biomedical Application

Zhang

et al. 2022

Applied Bionics and Biomechanics

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Magnetic-driven capsule robot has been widely studied due to its advantages of safety and reliability. However, when doctors carry out clinical examination, the capsule robot cannot achieve the ideal control effect due to the influence of the external magnetic field air gap. This paper is based on the kinetic energy theorem, combined with the principle of spiral mechanism in mechanical design foundation to construct a calculation method of energy utilization and to improve the control effect of capsule robot, suitable for the human gastrointestinal tract precise control of capsule robot to perform a variety of complex tasks. By calculating the energy utilization rate of the capsule robot under the control of external magnetic field, the method can improve the energy utilization rate by improving the equation parameters, so that the capsule robot can run according to the doctor’s ideal performance in practical application. Based on the analysis of the magnetic driven screw capsule robot, the model of the utilization rate of the external magnetic field of the capsule robot is established, and the fluid simulation of the capsule robot is carried out by using the method of computational fluid dynamics. The simulation results and experimental results show that the control effect of capsule robot can be improved by calculating the energy utilization rate of the robot, which is of great significance to human clinical examination and treatment.

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Section: System Configurationmentioning

confidence: 99%

A Magnetically Capsule Robot for Biomedical Application

Zhang

et al. 2022

Applied Bionics and Biomechanics

Self Cite

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“…[29][30][31] Therefore, an inverse kinematics model for obtaining the actuation field parameters according to the specific path trajectory still remains a challenge. [27,28,32] In the past decades, machine learning-based methods have been widely used to achieve higher precision control with lower computational costs. [33][34][35][36] As a powerful tool, it is utilized to learn nonlinear mapping relationships based on a large number of determined input and output data.…”

Section: Introductionmentioning

confidence: 99%

Data‐Driven Navigation of Ferromagnetic Soft Continuum Robots Based on Machine Learning

Sun

Zhang

et al. 2023

Advanced Intelligent Systems

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Ferromagnetic soft continuum robots (FSCRs) have great potential in biomedical applications due to their miniaturization and remote control capabilities. However, to direct the FSCR accurately and effectively, it is critical to realize inverse kinematics control in navigation, which is difficult for existing mechanical models. Herein, with the path segmentation strategy, an automatic method to navigate the FSCR in different paths based on machine learning is developed. A data‐driven artificial neural network (ANN) model to guide the steering of the magnetically responsive tip is presented. Using parametric simulations as the training data, the ANN model shows good generalization performance to predict control parameters. Moreover, the basic framework of the learning model remains effective when the FSCR materials change, which shows high scalability and is important for adapting to various environments. The study presents a promising strategy for guiding FSCRs in the narrow and tortuous vasculature, which is essential for many biomedical operations.

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