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The trajectory tracking control of 3-DOF instrument is very important for master-slave control robotic-assisted minimally invasive surgery. In this paper, dynamic structure and equation of motion for the 3-DOF instrument was established to use the Euler-Lagrange method based on screw theory. A control scheme is designed based on the computed-torque controller and a RBF neural network based compensating...
An exoskeleton system is a compact, light-weight robotic mechanism that a human can put-on for the purpose of overcoming inadequate muscle strength during the performance of physical tasks. In doing so, this integrated human-machine system offers multiple opportunities for creating assistive technologies that can be used in biomedical, industrial, aerospace and everyday life applications. The scope...
In this paper a new method of information fusion, Dezert-Smarandache theory (DSmT) is introduced to deal with high conflicting and uncertain information. And then the evidence reasoning machine (ERM) based on DSmT is presented for mobile robot mapping in unknown dynamic environment. Considering the characteristics of sonar sensors, the grid map method is adopted and a sonar sensor mathematical model...
This paper investigates emotion recognition from breath gas information. A breath gas sensing system is designed by using a quartz crystal resonator with a plasma-polymer film as a sensor. For computational experiment of emotion recognition, the machine learning-based approach, such as artificial neural network and support vector machine, is investigated. In emotion recognition experiments by using...
We propose a machine learning method of a TV cameraman's shooting technique with a neural network so that a robot camera can automatically shoot like an experienced cameraman. An experiment using a simulator that we developed shows that, by using our method, the cameraman's shooting technique can be quickly and easily embodied in the control system of the robot camera. Moreover, we derive guidelines...
Electroencephalography (EEG) is the reaction of the overall activities of the brain neurons. In the researches of Brain Computer Interface (BCI), the pattern recognition of EEG which is associated with mental tasks is the most important part of the BCI system. In this paper, data of ?? wave and ?? wave of C3, C4, P3 and P4 channels are certificated to be the proper sources for feature extraction,...
In order to resolve the problem incurred by low efficient manual classification of tremendous aurora images, an automatic aurora images classification system for huge dataset application is proposed. First, static aurora images are decomposed into texture part and cartoon part with a method called Morphological Component Analysis (MCA). Then features extracted from texture part are classified by three...
Pneumatic muscle actuators (PMA), owing to their obvious advantages over conventional linear actuators and pneumatic cylinders, have been recently used in the medical and industrial robotic applications. However, their potential has not been fully exploited due to their highly nonlinear and time dependent behavior. An attempt is being made in the proposed work to accurately predict the uncertain and...
This paper presents a neural network classifier based on fuzzy ARTMAP with conflict-resolving strategy. The proposed model explicitly resolves overlaps among prototypes of different classes through deploying a contraction procedure in the network, therefore, improving its generalization. Compared with other existing methods, the model has the priority of intuition and no parameter tuning. The performance...
Research of modern flight control methods for unmanned aerial vehicles (UAVs), which lower the cost and risk associated with the design of actual physical flight systems, has become research hotspot in recent years. However, design of control laws for UAV is complicated and challengeable due to UAV uncertainties, nonlinearity and coupling. This paper proposes a new hybrid controller design scheme,...
Research on thruster fault diagnosis of Underwater Robots (URs) is undertaken to improve its whole system reliability. Based on the BP neural network, a recurrent neural network (RNN) is presented and the network training algorithm is deduced. The RNN is trained by voyage head and yaw turning experiments, and the well trained network is applied to model for the URs. Compared the outputs between model...
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