Search results for "Artificial"
showing 10 items of 7394 documents
Calibration of mobile manipulators using 2D positional features.
2018
International audience; Robotic manipulators are increasingly being attached to Automatic Ground Vehicles (AGVs) to aid in the efficiency of assembly for manufacturing systems. However, calibrating these mobile manipulators is difficult as the offset between the robotic manipulator and the AGV is often unknown. This paper provides a novel, simple, and low-cost method for calibrating and measuring the performance of mobile manipulators by using data collected from a laser retroreflector that digitally detects the horizontal two-dimensional (2D) position of reflectors on an artifact as well as a navigation system that provides the heading angle and 2D position of the AGV. The method is mathem…
2021
Classification approaches that allow to extract logical rules such as decision trees are often considered to be more interpretable than neural networks. Also, logical rules are comparatively easy to verify with any possible input. This is an important part in systems that aim to ensure correct operation of a given model. However, for high-dimensional input data such as images, the individual symbols, i.e. pixels, are not easily interpretable. Therefore, rule-based approaches are not typically used for this kind of high-dimensional data. We introduce the concept of first-order convolutional rules, which are logical rules that can be extracted using a convolutional neural network (CNN), and w…
Food tray sealing fault detection using hyperspectral imaging and PCANet
2020
Abstract Food trays are very common in shops and supermarkets. Fresh food packaged in trays must be correctly sealed to protect the internal atmosphere and avoid contamination or deterioration. Due to the speed of production, it is not possible to have human quality inspection. Thus, automatic fault detection is a must to reach high production volume. This work describes a deep neural network based on Principal Component Analysis Network (PCANet) for food tray sealing fault detection. The input data come from hyperspectral cameras, showing more characteristics than regular industrial cameras or the human eye as they capture the spectral properties for each pixel. The proposed classification…
Designing Cognitive Cities
2018
The following text intends to give an introduction into some of the basic ideas which determined the conception of this book. Thus, the first part of this article introduces the terms “City”, “Smart City” and “Cognitive City”. The second part gives an overview of design theories and approaches such as Action Design Research and Ontological Design (a concept in-the-making), in order to deduce from a theoretical point of view some of the principles that needs to be taken into account when designing the Cognitive City. The third part highlights some concrete techniques that can be usefully applied to the problem of citizen communication for Cognitive Cities (namely Metaheuristics, Fuzzy Sets a…
Higher Degree F-transforms Based on B-splines of Two Variables
2016
The paper deals with the higher degree fuzzy transforms (F-transforms with polynomial components) for functions of two variables in the case when two-dimensional generalized fuzzy partition is given by B-splines of two variables. We investigate properties of the direct and inverse F-transform in this case and prove that using B-splines as basic functions of fuzzy partition allows us to improve the quality of approximation.
Selecting between CNC milling, robot milling and DMLS processes using a combined AHP and fuzzy approach
2017
Abstract Recent advancements in manufacturing technology allow now a much wider selection of machining processes. Milling with industrial robots or additive manufacturing could now replace traditional milling performed on CNC machine-tools, for certain applications. This work presents a decision-making process for selecting between CNC milling, robot milling and a process of additive manufacturing (DMLS) for a certain class of parts. The AHP method was used for selecting between the three variants of manufacturing processes. The criteria used for AHP were divided into crisp ones and criteria described by linguistic variables. For the last ones, fuzzy inference systems were built to extract …
Intelligent agents for feature modelling in computer aided design
2017
Abstract CAD modelling can be referred to as the process of generating an integrated multiple view model as a representation of multiple views of engineering design. In many situations, a change in the model of one view may conflict with the models of other views. In such situations, the model of some views needs to be adapted in order to make all models consistent. Thus, CAD models should be capable of adapting themselves to new situations. Recently, agent based technologies have been considered in order to increase both knowledge level and intelligence of real and virtual objects. The contribution of this paper consists in introducing the intelligent agents in intelligent CAD modelling. T…
Model-based Engineering for the Integration of Manufacturing Systems with Advanced Analytics
2016
To employ data analytics effectively and efficiently on manufacturing systems, engineers and data scientists need to collaborate closely to bring their domain knowledge together. In this paper, we introduce a domain-specific modeling approach to integrate a manufacturing system model with advanced analytics, in particular neural networks, to model predictions. Our approach combines a set of meta-models and transformation rules based on the domain knowledge of manufacturing engineers and data scientists. Our approach uses a model of a manufacturing process and its associated data as inputs, and generates a trained neural network model as an output to predict a quantity of interest. This pape…
Assembly Process Modeling Through Long Short-Term Memory
2021
This paper studies Long Short-Term Memory as a component of an adaptive assembly assistance system suggesting the next manufacturing step. The final goal is an assistive system able to help the inexperienced workers in their training stage or even experienced workers who prefer such support in their manufacturing activity. In contrast with the earlier analyzed context-based techniques, Long Short-Term Memory can be applied in unknown scenarios. The evaluation was performed on the data collected previously in an experiment with 68 participants assembling as target product a customizable modular tablet. We are interested in identifying the most accurate method of next assembly step prediction…
Fuzzy Modeling for Uncertain Nonlinear Systems Using Fuzzy Equations and Z-Numbers
2018
In this paper, the uncertainty property is represented by Z-number as the coefficients and variables of the fuzzy equation. This modification for the fuzzy equation is suitable for nonlinear system modeling with uncertain parameters. Here, we use fuzzy equations as the models for the uncertain nonlinear systems. The modeling of the uncertain nonlinear systems is to find the coefficients of the fuzzy equation. However, it is very difficult to obtain Z-number coefficients of the fuzzy equations.