Search results for "machine"
showing 10 items of 2592 documents
Making Industrial Robots Smarter with Adaptive Reasoning and Autonomous Thinking for Real-Time Tasks in Dynamic Environments: A Case Study
2018
In order to extend the abilities of current robots in industrial applications towards more autonomous and flexible manufacturing, this work presents an integrated system comprising real-time sensing, path-planning and control of industrial robots to provide them with adaptive reasoning, autonomous thinking and environment interaction under dynamic and challenging conditions. The developed system consists of an intelligent motion planner for a 6 degrees-of-freedom robotic manipulator, which performs pick-and-place tasks according to an optimized path computed in real-time while avoiding a moving obstacle in the workspace. This moving obstacle is tracked by a sensing strategy based on ma-chin…
Ant Colony Optimisation-Based Classification Using Two-Dimensional Polygons
2016
The application of Ant Colony Optimization to the field of classification has mostly been limited to hybrid approaches which attempt at boosting the performance of existing classifiers (such as Decision Trees and Support Vector Machines (SVM)) — often through guided feature reductions or parameter optimizations.
Use of second-order sliding mode observer for low-accuracy sensing in hydraulic machines
2018
Low-accuracy sensing is very common for the large hydraulic machines and does not allow for directly measuring the relative velocity which can be, otherwise, required for the control and monitoring purposes. This paper provides a case study of designing the second-order sliding mode observer based on the super-twisting robust exact differentiator. The nominal part of the system dynamics is derived from the simple available system measurements and incorporated into the observer structure. Parasitic by-effects, arising from the sensor sampling, quantization, and non-modeled distortions due to mechanical sensor interface, are shown as the main causes of hampering the final (steady-state) conve…
Adding Active Damping to Energy-Efficient Electro-Hydraulic Systems for Robotic Manipulators — Comparing Pressure and Acceleration Feedback
2020
The growing interest in energy efficiency, plug-and-play commissioning, and reduced maintenance for heavy-duty robotic manipulators directs towards self-contained, electro-hydraulic cylinders. These drives are characterized by extremely low damping that causes unwanted oscillations of the mechanical structure. Adding active damping to this class of energy-efficient architectures is essential. Hence, this paper bridges a literature gap by presenting a systematic comparison grounded on a model-based tuning of both pressure and acceleration feedback. It is shown that both approaches increase the system damping hugely and improve the performance of the linear system. Acceleration feedback shoul…
Machine Learning Approaches for Activity Recognition and/or Activity Prediction in Locomotion Assistive Devices—A Systematic Review
2020
Locomotion assistive devices equipped with a microprocessor can potentially automatically adapt their behavior when the user is transitioning from one locomotion mode to another. Many developments in the field have come from machine learning driven controllers on locomotion assistive devices that recognize/predict the current locomotion mode or the upcoming one. This review synthesizes the machine learning algorithms designed to recognize or to predict a locomotion mode in order to automatically adapt the behavior of a locomotion assistive device. A systematic review was conducted on the Web of Science and MEDLINE databases (as well as in the retrieved papers) to identify articles published…
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…
Minimal-model for robust control design of large-scale hydraulic machines
2018
Hydraulic machines are in use where the large forces, at relatively low velocities, are required by varying loads and often hazardous and hard-to-reach environments, like e.g. offshore, mining, forestry, cargo logistics, and others industries. Cranes and excavators equipped with multiple hydraulic cylinders are typical examples for that. For design of the robust feedback controls of hydraulic cylinders, already installed into large-scale machines, there is a general lack of reliable dynamic models. Also the suitable and feasible identification techniques, especially in frequency domain, yield limited. This paper proposes a minimal-modeling approach for determining the most relevant open-lo…
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…
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…
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…