scholarly journals Inverse Kinematic Solutions of Dual Redundant Camera Robot Based on Genetic Algorithm

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Libo Zhang ◽  
Jingjie He ◽  
Su Wang
Keyword(s):  
Genetic Algorithm ◽  
Objective Function ◽  
Efficient Algorithm ◽  
Degrees Of Freedom ◽  
Joint Space ◽  
Inverse Kinematic ◽  
Flexible Structure ◽  
Redundant Robot ◽  
Improvement Strategies ◽  
Physical Prototype

Inverse kinematic solutions for a dual redundant camera robot in position are examined in order to alleviate operation difficulty and reduce time. The inverse kinematic algorithm is based on a basic genetic algorithm, and the genetic algorithm which is used to solve the problem of a redundant robot is mainly optimized in the joint space. On this basis, the genetic algorithm improvement strategies are studied. In this paper, a genetic algorithm with constrained 2 redundant degrees of freedom (DOF) is proposed through setting 2 parameter variables, with more flexible structure of optimization objective function and more efficient algorithm than basic genetic algorithm. Finally, the result of inverse kinematic algorithm is achieved in terms of the physical prototype.

scholarly journals Hybrid Seven-bar Press Mechanism

2018 ◽  
Vol 12 (3) ◽  
pp. 181-187
Author(s):  
M. Erkan Kütük ◽  
L. Canan Dülger
Keyword(s):  
Genetic Algorithm ◽  
Objective Function ◽  
Design Optimization ◽  
Hybrid System ◽  
Degrees Of Freedom ◽  
Dimensional Synthesis ◽  
Design Variables ◽  
Optimization Study ◽  
Metal Stamping

An optimization study with kinetostatic analysis is performed on hybrid seven-bar press mechanism. This study is based on previous studies performed on planar hybrid seven-bar linkage. Dimensional synthesis is performed, and optimum link lengths for the mechanism are found. Optimization study is performed by using genetic algorithm (GA). Genetic Algorithm Toolbox is used with Optimization Toolbox in MATLAB®. The design variables and the constraints are used during design optimization. The objective function is determined and eight precision points are used. A seven-bar linkage system with two degrees of freedom is chosen as an example. Metal stamping operation with a dwell is taken as the case study. Having completed optimization, the kinetostatic analysis is performed. All forces on the links and the crank torques are calculated on the hybrid system with the optimized link lengths

scholarly journals Design of a Parallel Robotic Manipulator Using Evolutionary Computing

10.5772/50922 ◽  
2012 ◽  
Vol 9 (1) ◽  
pp. 27 ◽  
Author(s):  
António M. Lopes ◽  
E.J. Solteiro Pires ◽  
Manuel R. Barbosa
Keyword(s):  
Genetic Algorithm ◽  
Objective Function ◽  
Condition Number ◽  
Optimization Problem ◽  
Robotic Manipulator ◽  
Inverse Kinematic ◽  
Search Process ◽  
Algorithm Optimization ◽  
Structural Configuration ◽  
Optimization Search

In this paper the kinematic design of a 6-dof parallel robotic manipulator is analysed. Firstly, the condition number of the inverse kinematic jacobian is considered as the objective function, measuring the manipulator's dexterity and a genetic algorithm is used to solve the optimization problem. In a second approach, a neural network model of the analytical objective function is developed and subsequently used as the objective function in the genetic algorithm optimization search process. It is shown that the neuro-genetic algorithm can find close to optimal solutions for maximum dexterity, significantly reducing the computational burden. The sensitivity of the condition number in the robot's workspace is analysed and used to guide the designer in choosing the best structural configuration. Finally, a global optimization problem is also addressed.

scholarly journals Design of a cable-driven hyper-redundant robot with experimental validation

2017 ◽  
Vol 14 (5) ◽  
pp. 172988141773445 ◽  
Author(s):  
Lei Tang ◽  
Jungang Wang ◽  
Yang Zheng ◽  
Guoying Gu ◽  
Limin Zhu ◽  
...  
Keyword(s):  
Degrees Of Freedom ◽  
Mechanical Design ◽  
Load Capacity ◽  
Model Development ◽  
Joint Space ◽  
Kinematics Analysis ◽  
Test Bed ◽  
Real Time Control ◽  
Redundant Robot ◽  
Mechanism Model

This article presents a test bed for comprehensive study of a cable-driven hyper-redundant robot in terms of mechanical design, kinematics analysis, and experimental verification. To design the hyper-redundant robot, the multiple section structure is used. Each section consists of two rotational joints, a link mechanism, and three cables. In this sense, two degrees of freedom are achieved. For kinematics analysis between the actuator space and joint space, each section of the development is treated as three spherical–prismatic–spherical chains and a universal joint chain (3-SPS-U), which results in a four-chain parallel mechanism model. In order to obtain the forward kinematics from the joint space to task space directly and easily, the coordinate frames are established by the geometrical rules rather than the traditional Denavit–Hartenburg (D-H) rules. To solve the problem of inverse kinematics analysis, we utilize the product of exponentials approach. Finally, a prototype of 24-degrees of freedom hyper-redundant robot with 12 sections and 36 cables is fabricated and an experiment platform is built for real-time control of the robot. Different experiments in terms of trajectories tracking test, positioning accuracy test, and payload test are conducted for the validation of both mechanical design and model development. Experiment results demonstrate that the presented hyper-redundant robot has fine position accuracy, flexibility with mean position error less than 2%, and good load capacity.

Optimization of dynamic parameters for a traction-type passenger elevator using a dynamic byte coding genetic algorithm

2008 ◽  
Vol 223 (3) ◽  
pp. 595-605 ◽  
Author(s):  
D Mei ◽  
X Du ◽  
Z Chen
Keyword(s):  
Genetic Algorithm ◽  
Objective Function ◽  
Dynamic Model ◽  
Optimization Model ◽  
Degrees Of Freedom ◽  
Dynamic Performance ◽  
Optimal Solution ◽  
Dynamic Parameter ◽  
Dynamic Parameters ◽  
Encoding Method

To decrease the vibration and improve the dynamic performance of traction-type passenger elevators, an accurate vertical dynamic model with nine degrees of freedom for a gearless 2: 1 traction-type passenger elevator system is presented. Then, an optimization model of dynamic parameters for this type of passenger elevator is proposed based on the dynamic model. The optimization model takes the amplitude of vibration acceleration response of the elevator cage as the objective function. Various exciting forces and various working conditions can be considered by using corresponding weight coefficients in the objective function. To get higher efficiency and stronger robustness of optimized value, a dynamic byte coding genetic algorithm in solving the optimization model by combining the advantages of binary coding method with dynamic parameter encoding method is proposed, and the optimal solution is verified by sensitivity analysis. A practical engineering optimization for a 2: 1 traction-type passenger elevator system shows that the optimization model and method of dynamic parameters proposed in this article are effective.

Flexible Genetic Algorithm Based Optimal Power Flow of Power Systems

2018 ◽  
Vol 24 (3) ◽  
pp. 84
Author(s):  
Hassan Abdullah Kubba ◽  
Mounir Thamer Esmieel
Keyword(s):  
Genetic Algorithm ◽  
Objective Function ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Reactive Power ◽  
Test System ◽  
Multi Objective ◽  
Optimal Power ◽  
Blending Method ◽  
Real Coded Genetic Algorithm

Nowadays, the power plant is changing the power industry from a centralized and vertically integrated form into regional, competitive and functionally separate units. This is done with the future aims of increasing efficiency by better management and better employment of existing equipment and lower price of electricity to all types of customers while retaining a reliable system. This research is aimed to solve the optimal power flow (OPF) problem. The OPF is used to minimize the total generations fuel cost function. Optimal power flow may be single objective or multi objective function. In this thesis, an attempt is made to minimize the objective function with keeping the voltages magnitudes of all load buses, real output power of each generator bus and reactive power of each generator bus within their limits. The proposed method in this thesis is the Flexible Continuous Genetic Algorithm or in other words the Flexible Real-Coded Genetic Algorithm (RCGA) using the efficient GA's operators such as Rank Assignment (Weighted) Roulette Wheel Selection, Blending Method Recombination operator and Mutation Operator as well as Multi-Objective Minimization technique (MOM). This method has been tested and checked on the IEEE 30 buses test system and implemented on the 35-bus Super Iraqi National Grid (SING) system (400 KV). The results of OPF problem using IEEE 30 buses typical system has been compared with other researches.     

scholarly journals Optimal Placement and Sizing of D-STATCOM in Radial and Meshed Distribution Networks Using a Discrete-Continuous Version of the Genetic Algorithm

Electronics ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1452
Author(s):  
Cristian Mateo Castiblanco-Pérez ◽  
David Esteban Toro-Rodríguez ◽  
Oscar Danilo Montoya ◽  
Diego Armando Giral-Ramírez
Keyword(s):  
Genetic Algorithm ◽  
Objective Function ◽  
Programming Model ◽  
Distribution Networks ◽  
Optimization Method ◽  
Optimal Placement ◽  
Mixed Integer ◽  
Power Balance ◽  
Continuous Version ◽  
Discrete Part

In this paper, we propose a new discrete-continuous codification of the Chu–Beasley genetic algorithm to address the optimal placement and sizing problem of the distribution static compensators (D-STATCOM) in electrical distribution grids. The discrete part of the codification determines the nodes where D-STATCOM will be installed. The continuous part of the codification regulates their sizes. The objective function considered in this study is the minimization of the annual operative costs regarding energy losses and installation investments in D-STATCOM. This objective function is subject to the classical power balance constraints and devices’ capabilities. The proposed discrete-continuous version of the genetic algorithm solves the mixed-integer non-linear programming model that the classical power balance generates. Numerical validations in the 33 test feeder with radial and meshed configurations show that the proposed approach effectively minimizes the annual operating costs of the grid. In addition, the GAMS software compares the results of the proposed optimization method, which allows demonstrating its efficiency and robustness.

PERFORMANCE EVALUATION OF GENETIC DISTRIBUTED FUZZY CONTROLLERS FOR MULTI-PART-TYPE PRODUCTION LINE

2007 ◽  
Vol 06 (02) ◽  
pp. 115-128
Author(s):  
SEYED MAHDI HOMAYOUNI ◽  
TANG SAI HONG ◽  
NAPSIAH ISMAIL
Keyword(s):  
Genetic Algorithm ◽  
Performance Evaluation ◽  
Objective Function ◽  
Production Rate ◽  
Production Line ◽  
Production Systems ◽  
Membership Functions ◽  
Part Type ◽  
High Penalty ◽  
Single Part

Genetic distributed fuzzy (GDF) controllers are proposed for multi-part-type production line. These production systems can produce more than one part type. For these systems, "production rate" and "priority of production" for each part type is determined by production controllers. The GDF controllers have already been applied to single-part-type production systems. The methodology is illustrated and evaluated using a two-part-type production line. For these controllers, genetic algorithm (GA) is used to tune the membership functions (MFs) of GDF. The objective function of the GDF controllers minimizes the surplus level in production line. The results show that GDF controllers can improve the performance of production systems. GDF controllers show their abilities in reducing the backlog level. In production systems in which the backlog has a high penalty or is not allowed, the implementation of GDF controllers is advisable.

scholarly journals A New Approach of Soft Joint Based on a Cable-Driven Parallel Mechanism for Robotic Applications

Mathematics ◽  
2021 ◽  
Vol 9 (13) ◽  
pp. 1468
Author(s):  
Luis Nagua ◽  
Carlos Relaño ◽  
Concepción A. Monje ◽  
Carlos Balaguer
Keyword(s):  
Parallel Mechanism ◽  
Degrees Of Freedom ◽  
Kinematic Model ◽  
Experimental Tests ◽  
Humanoid Robots ◽  
Inverse Kinematic ◽  
Element Analysis ◽  
New Approach ◽  
Flexible Polymer ◽  
The Mathematical Model

A soft joint has been designed and modeled to perform as a robotic joint with 2 Degrees of Freedom (DOF) (inclination and orientation). The joint actuation is based on a Cable-Driven Parallel Mechanism (CDPM). To study its performance in more detail, a test platform has been developed using components that can be manufactured in a 3D printer using a flexible polymer. The mathematical model of the kinematics of the soft joint is developed, which includes a blocking mechanism and the morphology workspace. The model is validated using Finite Element Analysis (FEA) (CAD software). Experimental tests are performed to validate the inverse kinematic model and to show the potential use of the prototype in robotic platforms such as manipulators and humanoid robots.

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