scholarly journals Recent Developments on Modeling for a 3-DOF Micro-Hand Based on AI Methods

Micromachines ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 792
Author(s):  
Shuhei Kawamura ◽  
Mingcong Deng
Keyword(s):  
Artificial Intelligence ◽  
Degrees Of Freedom ◽  
Air Pressure ◽  
Support Vector ◽  
Input Output ◽  
Soft Actuator ◽  
Flexible Materials ◽  
Recent Developments ◽  
Soft Actuators ◽  
Three Degrees Of Freedom

Recently, soft actuators have been expected to have many applications in various fields. Most of the actuators are composed of flexible materials and driven by air pressure. The 3-DOF micro-hand, which is a kind of soft actuator, can realize a three degrees of freedom motion by changing the applied air pressure pattern. However, the input–output relation is nonlinear and complicated. In previous research, a model of the micro-hand was proposed, but an error between the model and the experimental results was large. In this paper, modeling for the micro-hand is proposed by using multi-output support vector regression (MSVR) and ant colony optimization (ACO), which is one of the artificial intelligence (AI) methods. MSVR estimates the input–output relation of the micro-hand. ACO optimizes the parameters of the MSVR model.

Dynamical Characteristics of a Hydraulic Soft Actuator With Three Degrees of Freedom

2021 ◽  
Author(s):  
Qing Xie ◽  
Tao Wang ◽  
Shiqiang Zhu
Keyword(s):  
Dynamic Model ◽  
Degrees Of Freedom ◽  
Soft Actuator ◽  
Dynamical Characteristics ◽  
Geometrical Features ◽  
Highly Nonlinear ◽  
Series Of Experiments ◽  
Soft Actuators ◽  
Modeling Of Dynamics ◽  
Three Degrees Of Freedom

Abstract In recent years, increasing attention and expanding research have been devoted to the study and application of soft actuators. Inherent compliance equips soft actuators with such advantages as incomparable flexibility, good environmental adaptability, safe interaction with the environment, etc. However, the highly nonlinear also bring challenges to modeling of dynamics. This study aims to explore the dynamical characteristics of an underwater hydraulic soft actuator. The actuator has three fiber-reinforced elastomer chambers distributed symmetrically inside. By controlling the pressure in the chambers through a hydraulic power system, the actuator can achieve spatial motion with three degrees of freedom. To describe the relationship between the input pressure combination and the actuator movement, a dynamic model considering the nonlinearity of viscoelastic material is developed based on Lagrangian method and constant curvature hypothesis. A series of experiments are carried out, including single-chamber actuation and multi-chamber actuation. The test results verify the effectiveness and precision of the model. Finally, the effects of the geometrical features on dynamic response are investigated through model-based simulation, which can provide guidance to parameter optimization. The proposed dynamic model can also contribute to behavior analysis, performance prediction, and motion control of the hydraulic soft actuator.

Design and modeling of a hydraulic soft actuator with three degrees of freedom

2020 ◽  
Vol 29 (12) ◽  
pp. 125017
Author(s):  
Qing Xie ◽  
Tao Wang ◽  
Shengda Yao ◽  
Zhipeng Zhu ◽  
Ning Tan ◽  
...  
Keyword(s):  
Degrees Of Freedom ◽  
Soft Actuator ◽  
Three Degrees Of Freedom

scholarly journals Artificial intelligence for diagnosis and prognosis in neuroimaging for dementia; a systematic review

2021 ◽  
Author(s):  
Robin J Borchert ◽  
Tiago Azevedo ◽  
Amanpreet Badhwar ◽  
Jose Bernal ◽  
Matthew Betts ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Systematic Review ◽  
Neurodegenerative Diseases ◽  
Structural Mri ◽  
Support Vector ◽  
Alzheimers Disease ◽  
Diagnosis And Prognosis ◽  
Lower Accuracy ◽  
Wide Range ◽  
Recent Developments

Introduction Recent developments in artificial intelligence (AI) and neuroimaging offer new opportunities for improving diagnosis and prognosis of dementia. To synthesise the available literature, we performed a systematic review. Methods We systematically reviewed primary research publications up to January 2021, using AI for neuroimaging to predict diagnosis and/or prognosis in cognitive neurodegenerative diseases. After initial screening, data from each study was extracted, including: demographic information, AI methods, neuroimaging features, and results. Results We found 2709 reports, with 252 eligible papers remaining following screening. Most studies relied on the Alzheimers Disease Neuroimaging Initiative (ADNI) dataset (n=178) with no other individual dataset used more than 5 times. Algorithmic classifiers, such as support vector machine (SVM), were the most commonly used AI method (47%) followed by discriminative (32%) and generative (11%) classifiers. Structural MRI was used in 71% of studies with a wide range of accuracies for the diagnosis of neurodegenerative diseases and predicting prognosis. Lower accuracy was found in studies using a multi-class classifier or an external cohort as the validation group. There was improvement in accuracy when neuroimaging modalities were combined, e.g. PET and structural MRI. Only 17 papers studied non-Alzheimers disease dementias. Conclusion The use of AI with neuroimaging for diagnosis and prognosis in dementia is a rapidly emerging field. We make a number of recommendations addressing the definition of key clinical questions, heterogeneity of AI methods, and the availability of appropriate and representative data. We anticipate that addressing these issues will enable the field to move towards meaningful clinical translation.

Decoupling Control of Three Degrees of Freedom Hybrid Magnetic Bearing Based on LS-SVM

2014 ◽  
Vol 529 ◽  
pp. 534-538
Author(s):  
Yuan Yuan Li ◽  
Huang Qiu Zhu
Keyword(s):  
Degrees Of Freedom ◽  
Control Method ◽  
Hybrid Control ◽  
Original System ◽  
Magnetic Bearing ◽  
Inverse System ◽  
Least Square ◽  
Decoupling Control ◽  
Support Vector ◽  
Three Degrees Of Freedom

In the paper, the decoupling control method based on least square support vector machine (LS-SVM) inverse system is proposed, and adopting the method realizes decoupling control of an AC-DC three degrees of freedom hybrid magnetic bearing (AC-DC-3DOF-HMB). Aimed at the complicated multivariate nonlinear, strong coupling system of the AC-DC-3DOF-HMB, the reversibility of original system was analyzed, by the ability of least square support vector machines (LS-SVM) in universal approximation and identification fitting to get inverse model of AC-DC three degrees of freedom hybrid magnetic bearing. Then according to the basic principle of inverse system method, the inverse system was connected with the original system. So the complex nonlinear multivariable system is decoupled into three independent pseudo-linear system. The simulation results show that the system was decoupled; the hybrid control method has good dynamic and static performance, verify the feasibility of the proposed control method.

scholarly journals An Origami Flexiball-Inspired Metamaterial Actuator and Its In-Pipe Robot Prototype

Actuators ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 67
Author(s):  
Fuwen Hu ◽  
Tian Li
Keyword(s):  
Degrees Of Freedom ◽  
Three Dimensional ◽  
Multiple Degrees Of Freedom ◽  
Soft Actuator ◽  
Structure Building ◽  
Magnetically Actuated ◽  
Mechanical Metamaterials ◽  
New Type ◽  
Soft Actuators ◽  
Magnetoactive Elastomer

Usually, polyhedra are viewed as the underlying constructive cells of packing or tilling in many disciplines, including crystallography, protein folding, viruses structure, building architecture, etc. Here, inspired by the flexible origami polyhedra (commonly called origami flexiballs), we initially probe into their intrinsic metamaterial properties and robotized methods from fabrication to actuation. Firstly, the topology, geometries and elastic energies of shape shifting are analyzed for the three kinds of origami flexiballs with extruded outward rhombic faces. Provably, they meet the definitions of reconfigurable and transformable metamaterials with switchable stiffness and multiple degrees of freedom. Secondly, a new type of soft actuator with rhombic deformations is successfully put forward, different from soft bionic deformations like elongating, contracting, bending, twisting, spiraling, etc. Further, we redesign and fabricate the three-dimensional (3D) printable structures of origami flexiballs considering their 3D printability and foldability, and magnetically actuated them through the attachment of magnetoactive elastomer. Lastly, a fully soft in-pipe robot prototype is presented using the origami flexiball as an applicable attempt. Experimental work clearly suggests that the presented origami flexiball robot has good adaptability to various pipe sizes, and also can be easily expanded to different scales, or reconfigured into more complex metastructures by assembly. In conclusion, this research provides a newly interesting and illuminating member for the emerging families of mechanical metamaterials, soft actuators and soft robots.

Control of a Class of Manipulators With a Single Flexible Link: Part I—Feedback Linearization

1991 ◽  
Vol 113 (4) ◽  
pp. 655-661 ◽  
Author(s):  
D. Wang ◽  
M. Vidyasagar
Keyword(s):  
Feedback Linearization ◽  
Degrees Of Freedom ◽  
Input State ◽  
Asymptotically Stable ◽  
Input Output ◽  
Flexible Link ◽  
State Equations ◽  
The Subject ◽  
Three Degrees Of Freedom ◽  
Linearization Techniques

The subject of this paper is the feedback linearization of the input-output and input-state equations for a class of multi-link, three degrees-of-freedom manipulators with the last link flexible. This class includes the 5-bar-linkage and the elbow manipulator. It is shown that the input-output equations are only feedback linearizable if the output variables are chosen appropriately. However, the nonlinear dynamics made unobservable by this feedback are not asymptotically stable which is a severe drawback. It is then shown that the input-state equations are not feedback linearizable. These results indicate that feedback linearization techniques are not appropriate for this class of manipulators. Thus, alternate methodologies should be explored. That issue is tackled in Part II.

Virtual Screening Meets Deep Learning

2018 ◽  
Vol 15 (1) ◽  
pp. 6-28 ◽  
Author(s):  
Javier Pérez-Sianes ◽  
Horacio Pérez-Sánchez ◽  
Fernando Díaz
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Deep Learning ◽  
Virtual Screening ◽  
Great Increase ◽  
New Drugs ◽  
Learning Approach ◽  
Screening Strategies ◽  
Computer Aided ◽  
Recent Developments

Background: Automated compound testing is currently the de facto standard method for drug screening, but it has not brought the great increase in the number of new drugs that was expected. Computer- aided compounds search, known as Virtual Screening, has shown the benefits to this field as a complement or even alternative to the robotic drug discovery. There are different methods and approaches to address this problem and most of them are often included in one of the main screening strategies. Machine learning, however, has established itself as a virtual screening methodology in its own right and it may grow in popularity with the new trends on artificial intelligence. Objective: This paper will attempt to provide a comprehensive and structured review that collects the most important proposals made so far in this area of research. Particular attention is given to some recent developments carried out in the machine learning field: the deep learning approach, which is pointed out as a future key player in the virtual screening landscape.

scholarly journals Active Disturbance Rejection for a Three Degrees of Freedom Gyroscope

2018 ◽  
Vol 51 (13) ◽  
pp. 372-377 ◽  
Author(s):  
Juan E. Andrade García ◽  
Alejandra Ferreira de Loza ◽  
Luis T. Aguilar ◽  
Ramón I. Verdés
Keyword(s):  
Disturbance Rejection ◽  
Degrees Of Freedom ◽  
Active Disturbance Rejection ◽  
Three Degrees Of Freedom
Sign in / Sign up

Export Citation Format

Share Document