scholarly journals Applying BAT Evolutionary Optimization to Image-Based Visual Servoing

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Marco Perez-Cisneros ◽  
Gerardo Garcia-Gil ◽  
Sabrina Vega-Maldonado ◽  
J. Arámburo-Lizárraga ◽  
Erik Cuevas ◽  
...  
Keyword(s):  
Predictive Control ◽  
Visual Servoing ◽  
Optimization Problem ◽  
Evolutionary Optimization ◽  
Interaction Matrix ◽  
Trajectory Data ◽  
Control Task ◽  
Prediction Scheme ◽  
Reliable Model ◽  
Image Prediction

This paper presents a predictive control strategy for an image-based visual servoing scheme that employs evolutionary optimization. The visual control task is approached as a nonlinear optimization problem that naturally handles relevant visual servoing constraints such as workspace limitations and visibility restrictions. As the predictive scheme requires a reliable model, this paper uses a local model that is based on the visual interaction matrix and a global model that employs 3D trajectory data extracted from a quaternion-based interpolator. The work assumes a free-flying camera with 6-DOF simulation whose results support the discussion on the constraint handling and the image prediction scheme.

Visual Servoing of Automatic Alignment System Using Model Predictive Control

2014 ◽  
Vol 625 ◽  
pp. 627-632
Author(s):  
Chi Ying Lin ◽  
Yu Sheng Zeng
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Visual Servoing ◽  
Optimization Problem ◽  
Rapid Development ◽  
Economic Benefits ◽  
Image Feature ◽  
Alignment System ◽  
Control Command ◽  
Automatic Alignment

Over the past few decades, vision based alignment has been accepted as an important technique to achieve higher economic benefits for precision manufacturing and measurement applications. Also referred to as visual servoing, this technique basically applies the vision feedback information and drives the moving parts to the desired target location using some appropriate control laws. Although recently rapid development of advanced image processing algorithms and hardware have made this alignment process an easier task, some fundamental issues including inevitable system constraints and singularities, still remain as a challenging research topic for further investigation. This paper aims to develop a visual servoing method for automatic alignment system using model predictive control (MPC). The reason for using this optimal control for visual servoing design is because of its capability of handling constraints such as motor and image constraints in precision alignment systems. In particular, a microassembly system for peg and hole alignment application is adopted to illustrate the design process. The goal is to perform visual tracking of two image feature points based on a XYθ motor-stage system. From the viewpoint of MPC, this is an optimization problem that minimizes feature errors under given constraints. Therefore, a dynamic model consisting of camera parameters and motion stage dynamics is first derived to build the prediction model and set up the cost function. At each sample step the control command is obtained by solving a quadratic programming optimization problem. Finally, simulation results with comparison to a conventional image based visual servoing method demonstrate the effectiveness and potential use of this method.

scholarly journals Designing Strong Privacy Metrics Suites Using Evolutionary Optimization

2021 ◽  
Vol 24 (2) ◽  
pp. 1-35
Author(s):  
Isabel Wagner ◽  
Iryna Yevseyeva
Keyword(s):  
Optimization Problem ◽  
Evolutionary Optimization ◽  
Multiple Objectives ◽  
Shared Value ◽  
Vehicular Communications ◽  
Open Problems ◽  
Value Range ◽  
Genomic Privacy ◽  
Metaheuristic Optimization Algorithms ◽  
Selection Of

The ability to measure privacy accurately and consistently is key in the development of new privacy protections. However, recent studies have uncovered weaknesses in existing privacy metrics, as well as weaknesses caused by the use of only a single privacy metric. Metrics suites, or combinations of privacy metrics, are a promising mechanism to alleviate these weaknesses, if we can solve two open problems: which metrics should be combined and how. In this article, we tackle the first problem, i.e., the selection of metrics for strong metrics suites, by formulating it as a knapsack optimization problem with both single and multiple objectives. Because solving this problem exactly is difficult due to the large number of combinations and many qualities/objectives that need to be evaluated for each metrics suite, we apply 16 existing evolutionary and metaheuristic optimization algorithms. We solve the optimization problem for three privacy application domains: genomic privacy, graph privacy, and vehicular communications privacy. We find that the resulting metrics suites have better properties, i.e., higher monotonicity, diversity, evenness, and shared value range, than previously proposed metrics suites.

scholarly journals Evolutionary Optimization of Case-Based Forecasting Algorithms in Chaotic Environments

Symmetry ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 301
Author(s):  
Alexander Musaev ◽  
Ekaterina Borovinskaya
Keyword(s):  
Chaotic Dynamics ◽  
Evolutionary Optimization ◽  
Modeling Method ◽  
Dynamic Adaptation ◽  
Evolutionary Modeling ◽  
Computational Schemes ◽  
Prediction Algorithms ◽  
Prediction Scheme ◽  
Case Based

The problem of dynamic adaptation of prediction algorithms in chaotic environments based on identification of the situations-analogs in the database of retrospective observations is considered. Under conditions of symmetrical and unsymmetrical chaotic dynamics, traditional computational schemes of precedent prediction turn out to be ineffective. In this regard, a dynamic adaptation of precedent analysis algorithms based on the method of evolutionary modeling is proposed. Implementation of the computational precedent prediction scheme for chaotic processes as well as the evolutionary modeling method are described.

scholarly journals 2D Legendre Moments-Based Visual Control

2012 ◽  
Vol 162 ◽  
pp. 487-496 ◽  
Author(s):  
Aurelien Yeremou Tamtsia ◽  
Youcef Mezouar ◽  
Philippe Martinet ◽  
Haman Djalo ◽  
Emmanuel Tonye
Keyword(s):  
Visual Servoing ◽  
Dynamic Range ◽  
High Sensitivity ◽  
High Dynamic Range ◽  
Interaction Matrix ◽  
Geometric Moments ◽  
Control Scheme ◽  
Control Schemes ◽  
Legendre Moments ◽  
Set Of Points

Among region-based descriptors, geometric moments have been widely exploited to design visual servoing schemes. However, they present several disadvantages such as high sensitivity to noise measurement, high dynamic range and information redundancy (since they are not computed onto orthogonal basis). In this paper, we propose to use a class of orthogonal moments (namely Legendre moments) instead of geometric moments to improve the behavior of moment-based control schemes. The descriptive form of the interaction matrix related to the Legendre moments computed from a set of points is rst derived. Six visual features are then selected to design a partially-decoupled control scheme. Finally simulated and experimental results are presented to illustrate the validity of our proposal.

Niche Genetic Algorithm Based on Sexual Reproduction and Multimodal Function Optimization Problem

2013 ◽  
pp. 8-16
Author(s):  
Yulong Tian ◽  
Tao Gao ◽  
Weifang Zhai ◽  
Yaying Hu ◽  
Xinfeng Li
Keyword(s):  
Genetic Algorithm ◽  
Sexual Reproduction ◽  
Optimization Problem ◽  
Optimization Problems ◽  
Evolutionary Optimization ◽  
Function Optimization ◽  
Premature Convergence ◽  
Multimodal Functions ◽  
Multimodal Function Optimization ◽  
Multimodal Function

In this paper, a genetic algorithm with sexual reproduction and niche selection technology is proposed. Simple genetic algorithm has been successfully applied to many evolutionary optimization problems. But there is a problem of premature convergence for complex multimodal functions. To solve it, the frame and realization of niche genetic algorithm based on sexual reproduction are presented. Age and sexual structures are given to the individuals referring the sexual reproduction and “niche” phenomena, importing the niche selection technology. During age and sexual operators, different evolutionary parameters are given to the individuals with different age and sexual structures. As a result, this genetic algorithm can combat premature convergence and keep the diversity of population. The testing for Rastrigin function and Shubert function proves that the niche genetic algorithm based on sexual reproduction is effective.

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