Kinematic Control for Crossed-Fiber-Reinforced Soft Manipulator Using Sparse Bayesian Learning

Shen, Yi; Deng, Linan; Yuan, Ye; Zhang, Fumin; Ding, Han

doi:10.1109/tmech.2022.3142940

Cited by 10 publications

(6 citation statements)

References 35 publications

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“…For a reasonable comparison of the performance of the controllers, the parameters of the three controllers are the same. Sliding mode surface parameters: 1…”

Section: Simulation Resultsmentioning

confidence: 99%

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Adaptive Fractional-Order Non-Singular Fast Terminal Sliding Mode Control Based on Fixed Time Disturbance Observer for Manipulators

Zhang

Quan

2022

IEEE Access

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In this study, with the help of a disturbance observer, an adaptive fractional-order sliding mode control scheme is designed to achieve trajectory tracking control of indeterminate manipulators. Firstly, the fractional-order non-singular fast terminal sliding mode (FO-NFTSM) surface is presented to increase the convergence velocity of the controller. Secondly, the adaptive reaching law is designed on the strength of the super-twisting algorithm to ensure the control performance of the approaching stage. Meanwhile, aiming at the compound disturbance existing in the manipulator system, an adaptive fixed-time sliding mode disturbance observer (AFSMDO) is introduced to settle the problem, which can estimate the lumped disturbance in real-time. Moreover, compensate for the system and raise the precision of the controller. The Lyapunov method is applied to certify the stability of the control system. Simulation experiments verify the superior property of the controller designed in this article.

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“…For a reasonable comparison of the performance of the controllers, the parameters of the three controllers are the same. Sliding mode surface parameters: 1…”

Section: Simulation Resultsmentioning

confidence: 99%

“…As one of the most widely used mechanical devices in the field of robotics, the manipulator is widely used in important fields such as aerospace, military, manufacturing, and medical [1][2][3][4]. The trajectory tracking control of the manipulator has always been a hot research direction.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Fractional-Order Non-Singular Fast Terminal Sliding Mode Control Based on Fixed Time Disturbance Observer for Manipulators

Zhang

Quan

2022

IEEE Access

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“…The relationship between the cable driving force of the bioinspired fishbone unit and its bending angle was established (equation ( 34)). Equation (34) provides a guide for determining the geometry and dimensions of the continuum robot according to the engineering feasibility, minimum material consumption, and minimum driving force principles. We will optimize the continuum robot according to the specific application requirements and working environment in the future.…”

Section: Discussionmentioning

confidence: 99%

“…Fast response, compact design, and Larger required driving force [2,5,8,[28][29][30] providing both tension and thrust due to the larger stiffness of the driving rod, imperfect flexibility, and inconvenience for the multi-section design Pneumatic actuation Easy implementation, mature Low precision and [13,20,[32][33][34][35] technology, low cost, and lighter inconvenience for long-distance transmission due to nonlinear response, gas leakage, and gas compressibility…”

Section: Rod Drivenmentioning

confidence: 99%

A bioinspired fishbone continuum robot with rigid-flexible-soft coupling structure

Zhou¹,

Yao²,

Zhang³

et al. 2022

Bioinspir. Biomim.

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Rigid-flexible-soft coupled robots are an important development direction of robotics, which face many theoretical and technical challenges in design, manufacturing, and modeling. Inspired by fishbones, we propose a novel cable-driven single-backbone continuum robot which has compact structure, light weight, and high dexterity. Different from the existing single-backbone continuum robot, the middle backbone of the continuum robot is serially formed by multiple cross-arranged bioinspired fishbone units. The proposed bioinspired fishbone unit having good one-dimensional bending properties is a special rigid-flexible-soft structure mainly made by multi-material 3D printing technology. The unique design and manufacturing of the middle backbone bring the continuum robot excellent constant curvature characteristics and reduce the coupling between different motion dimensions, laying a foundation for the continuum robot to have a more accurate theoretical model as well as regular and controllable deformation. Moreover, we build the forward and inverse kinematics model based on the geometric analysis method, and analyze its workspace. Further, the comparison between the experimental and theoretical results shows that the prediction errors of the kinematics model are within desired 0.5 mm. Also, we establish the relation between the cable driving force of the bioinspired fishbone unit and its bending angle which can provide a guidance for the optimization of the continuum robot in the future. The application demos prove that the continuum robot has good dexterity and compliance, and can perform tasks such as obstacle crossing locomotion and narrow space transportation. This work provides new ideas for the bioinspired design and high-precision modeling of continuum robots.

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“…Although this method can reproduce more accurate IKM in a free environment, it still cannot solve the problem of deformation error when the soft manipulator interacts with obstacles. Yi Shen et al [24] proposed a segmented constant curvature motion model based on sparse Bayesian learning, and designed a feedback controller based on this model. However, this experiment was conducted under offline conditions of a soft manipulator without load, and this method does not have the ability to update model parameters online in real-time based on changes in the environment and load.…”

Section: Introductionmentioning

confidence: 99%

Research on Inverse Dynamics modeling of Soft Manipulator

Geng,

He,

Yang

et al. 2024

Preprint

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In recent years, soft manipulators have attracted much attention in the field of robotics research due to their dexterity and good environmental adaptability. However, accurately modeling of soft manipulators remains a difficult task due to the uncertainties in their dynamics. Therefore, this paper proposed an method to accurately model the inverse dynamics of a soft manipulator. A BP neural network model was used to establish the inverse dynamics model of the soft manipulator, and then the particle swarm optimization (PSO) algorithm was employed to optimize the initial weights and biases of the BP neural network, and finally the correspondence between the end position of the soft manipulator and the input air pressure was established. In addition, load weights were introduced as one of the network inputs to enhance the control accuracy of the soft manipulator when it carries a load. By trajectory tracking experiments with and without load, the method was proved to achieve an average end position error of 0.839 mm with a relative error of 0.98%. When carrying loads its average end error is 1.800 mm with a relative error of 2.12%. The results demonstrated that the proposed optimized method can effectively improve the accuracy of the soft manipulator under both no-load and load conditions.

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Kinematic Control for Crossed-Fiber-Reinforced Soft Manipulator Using Sparse Bayesian Learning

Cited by 10 publications

References 35 publications

Adaptive Fractional-Order Non-Singular Fast Terminal Sliding Mode Control Based on Fixed Time Disturbance Observer for Manipulators

Adaptive Fractional-Order Non-Singular Fast Terminal Sliding Mode Control Based on Fixed Time Disturbance Observer for Manipulators

A bioinspired fishbone continuum robot with rigid-flexible-soft coupling structure

Research on Inverse Dynamics modeling of Soft Manipulator

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