Search results for " network"
showing 10 items of 6428 documents
Underwater Wireless Communications for Cooperative Robotics with UWSim-NET
2019
The increasing number of autonomous underwater vehicles (AUVs) cooperating in underwater operations has motivated the use of wireless communications. Their modeling can minimize the impact of their limited performance in real-time robotic interventions. However, robotic frameworks hardly ever consider the communications, and network simulators are not suitable for HIL experiments. In this work, the UWSim-NET is presented, an open source tool to simulate the impact of communications in underwater robotics. It gathers the benefits of NS3 in modeling communication networks with those of the underwater robot simulator (UWSim) and the robot operating system (ROS) in modeling robotic systems. Thi…
End-to-end congestion control protocols for remote programming of robots, using heterogeneous networks: A comparative analysis
2008
There are many interesting aspects of Internet Telerobotics within the network robotics context, such as variable bandwidth and time-delays. Some of these aspects have been treated in the literature from the control point of view. Moreover, only a little work is related to the way Internet protocols can help to minimize the effect of delay and bandwidth fluctuation on network robotics. In this paper, we present the capabilities of TCP, UDP, TCP Las Vegas, TEAR, and Trinomial protocols, when performing a remote experiment within a network robotics application, the UJI Industrial Telelaboratory. Comparative analysis is presented through simulations within the NS2 platform. Results show how th…
A non-stationary relay-based 3D MIMO channel model with time-variant path gains for human activity recognition in indoor environments
2021
AbstractExtensive research showed that the physiological response of human tissue to exposure to low-frequency electromagnetic fields is the induction of an electric current in the body segments. As a result, each segment of the human body behaves as a relay, which retransmits the radio-frequency (RF) signal. To investigate the impact of this phenomenon on the Doppler characteristics of the received RF signal, we introduce a new three-dimensional (3D) non-stationary channel model to describe the propagation phenomenon taking place in an indoor environment. Here, the indoor space is equipped with a multiple-input multiple-output (MIMO) system. A single person is moving in the indoor space an…
Adaptive Neural Control of MIMO Nonstrict-Feedback Nonlinear Systems with Time Delay
2016
In this paper, an adaptive neural output-feedback tracking controller is designed for a class of multiple-input and multiple-output nonstrict-feedback nonlinear systems with time delay. The system coefficient and uncertain functions of our considered systems are both unknown. By employing neural networks to approximate the unknown function entries, and constructing a new input-driven filter, a backstepping design method of tracking controller is developed for the systems under consideration. The proposed controller can guarantee that all the signals in the closed-loop systems are ultimately bounded, and the time-varying target signal can be tracked within a small error as well. The main con…
Summarizing Large Scale 3D Point Cloud for Navigation Tasks
2017
International audience; Democratization of 3D sensor devices makes 3D maps building easier especially in long term mapping and autonomous navigation. In this paper we present a new method for summarizing a 3D map (dense cloud of 3D points). This method aims to extract a summary map facilitating the use of this map by navigation systems with limited resources (smartphones, cars, robots...). This Vision-based summarizing process is applied in a fully automatic way using the photometric, geometric and semantic information of the studied environment.
Robust link prediction in criminal networks: A case study of the Sicilian Mafia
2020
Abstract Link prediction exercises may prove particularly challenging with noisy and incomplete networks, such as criminal networks. Also, the link prediction effectiveness may vary across different relations within a social group. We address these issues by assessing the performance of different link prediction algorithms on a mafia organization. The analysis relies on an original dataset manually extracted from the judicial documents of operation “Montagna”, conducted by the Italian law enforcement agencies against individuals affiliated with the Sicilian Mafia. To run our analysis, we extracted two networks: one including meetings and one recording telephone calls among suspects, respect…
2D/3D Object Recognition and Categorization Approaches for Robotic Grasping
2017
International audience; Object categorization and manipulation are critical tasks for a robot to operate in the household environment. In this paper, we propose new methods for visual recognition and categorization. We describe 2D object database and 3D point clouds with 2D/3D local descriptors which we quantify with the k-means clustering algorithm for obtaining the Bag of Words (BOW). Moreover, we develop a new global descriptor called VFH-Color that combines the original version of Viewpoint Feature Histogram (VFH) descriptor with the color quantization histogram, thus adding the appearance information that improves the recognition rate. The acquired 2D and 3D features are used for train…
Multiple Fault Diagnosis of Electric Powertrains Under Variable Speeds Using Convolutional Neural Networks
2018
Electric powertrains are widely used in automotive and renewable energy industries. Reliable diagnosis for defects in the critical components such as bearings, gears and stator windings, is important to prevent failures and enhance the system reliability and power availability. Most of existing fault diagnosis methods are based on specific characteristic frequencies to single faults at constant speed operations. Once multiple faults occur in the system, such a method may not detect the faults effectively and may give false alarms. Furthermore, variable speed operations render a challenge of analysing nonstationary signals. In this work, a deep learning-based fault diagnosis method is propos…
Predictive Model Markup Language (PMML) Representation of Bayesian Networks: An Application in Manufacturing
2018
International audience; Bayesian networks (BNs) represent a promising approach for the aggregation of multiple uncertainty sources in manufacturing networks and other engineering systems for the purposes of uncertainty quantification, risk analysis, and quality control. A standardized representation for BN models will aid in their communication and exchange across the web. This article presents an extension to the predictive model markup language (PMML) standard for the representation of a BN, which may consist of discrete variables, continuous variables, or their combination. The PMML standard is based on extensible markup language (XML) and used for the representation of analytical models…
Weld quality prediction in linear friction welding of AA6082-T6 through an integrated numerical tool
2016
Abstract A numerical and an experimental campaign were carried out with varying oscillation frequency and interface pressure. The local values of the main field variables at the contact interface between the specimens were predicted by a Lagrangian, implicit, thermo-mechanical FEM model and used as input of a dedicated Neural Network (NN). The NN, integrated in the FEM environment, was designed in order to calculate both a Boolean output, indicating the occurrence of welding, and a continuous output, indicating the quality of the obtained solid state weld. The analysis of the obtained results allowed three different levels of bonding quality, i.e., no weld, sound weld and excess of heat, to…