Search results for " applications."
showing 10 items of 4344 documents
Extreme minimal learning machine: Ridge regression with distance-based basis
2019
The extreme learning machine (ELM) and the minimal learning machine (MLM) are nonlinear and scalable machine learning techniques with a randomly generated basis. Both techniques start with a step in which a matrix of weights for the linear combination of the basis is recovered. In the MLM, the feature mapping in this step corresponds to distance calculations between the training data and a set of reference points, whereas in the ELM, a transformation using a radial or sigmoidal activation function is commonly used. Computation of the model output, for prediction or classification purposes, is straightforward with the ELM after the first step. In the original MLM, one needs to solve an addit…
Accelerated bearing life-Time test rig development for low speed data acquisition
2017
Condition monitoring plays an important role in rotating machinery to ensure reliability of the equipment, and to detect fault conditions at an early stage. Although health monitoring methodologies have been thoroughly developed for rotating machinery, low-speed conditions often pose a challenge due to the low signal-to-noise ratio. To this aim, sophisticated algorithms that reduce noise and highlight the bearing faults are necessary to accurately diagnose machines undergoing this condition. In the development phase, sensor data from a healthy and damaged bearing rotating at low-speed is required to verify the performance of such algorithms. A test rig for performing accelerated life-time t…
Towards a Reference Architecture for Archival Systems: Use Case With Product Data
2014
Long-term preservation of product data is imperative for many organizations. A product data archive should be designed to ensure information accessibility and understanding over time. Approaches, such as the Open Archival Information System Reference Model (OAIS RM) and the Audit and Certification of Trustworthy Digital Repositories (ACTDR), provide a framework for conceptually describing and evaluating archives. These approaches are generic and do not focus on particular contexts or content types such as product data. Moreover, these approaches offer no guidance on how to formally and comprehensively describe archival systems. Such descriptions should include the business activities that a…
On Stability of Virtual Torsion Sensor for Control of Flexible Robotic Joints with Hysteresis
2019
Author's accepted manuscript (postprint). This article has been published in a revised form in Robotica, http://doi.org/10.1017/S0263574719001358. This version is free to view and download for private research and study only. Not for re-distribution or re-use. © 2019 Cambridge University Press. Available from 25/03/2020. Aim of the virtual torsion sensor (VTS) is in observing the nonlinear deflection in the flexible joints of robotic manipulators and, by its use, improving positioning control of the joint load. This model-based approach utilizes the motor-side sensing only and, therefore, replaces the load-side encoders at nearly zero hardware costs. For being applied in the closed control …
Visual contact with catadioptric cameras
2015
Abstract Time to contact or time to collision (TTC) is utmost important information for animals as well as for mobile robots because it enables them to avoid obstacles; it is a convenient way to analyze the surrounding environment. The problem of TTC estimation is largely discussed in perspective images. Although a lot of works have shown the interest of omnidirectional camera for robotic applications such as localization, motion, monitoring, few works use omnidirectional images to compute the TTC. In this paper, we show that TTC can be also estimated on catadioptric images. We present two approaches for TTC estimation using directly or indirectly the optical flow based on de-rotation strat…
Hankelet-based action classification for motor intention recognition
2017
Powered lower-limb prostheses require a natural, and an easy-to-use, interface for communicating amputee’s motor intention in order to select the appropriate motor program in any given context, or simply to commute from active (powered) to passive mode of functioning. To be widely accepted, such an interface should not put additional cognitive load at the end-user, it should be reliable and minimally invasive. In this paper we present a one such interface based on a robust method for detecting and recognizing motor actions from a low-cost wearable sensor network mounted on a sound leg providing inertial (accelerometer, gyrometer and magnetometer) data in real-time. We assume that the sensor…
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…
Real-time biomechanical modeling of the liver using Machine Learning models trained on Finite Element Method simulations
2020
[EN] The development of accurate real-time models of the biomechanical behavior of different organs and tissues still poses a challenge in the field of biomechanical engineering. In the case of the liver, specifically, such a model would constitute a great leap forward in the implementation of complex applications such as surgical simulators, computed-assisted surgery or guided tumor irradiation. In this work, a relatively novel approach for developing such a model is presented. It consists in the use of a machine learning algorithm, which provides real-time inference, trained on tens of thousands of simulations of the biomechanical behavior of the liver carried out by the finite element me…
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…
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…