scholarly journals Optimization of H4 Parallel Manipulator Using Genetic Algorithm

10.5772/32428 ◽  
2012 ◽  
Author(s):  
M. Falahian ◽  
H.M. Daniali ◽  
S.M. Varedi
Keyword(s):  
Genetic Algorithm ◽  
Parallel Manipulator

Multi-Objective Optimization of a 2-DoF Purely Translational Parallel Manipulator

2011 ◽  
Vol 317-319 ◽  
pp. 794-798
Author(s):  
Zhi Bin Li ◽  
Yun Jiang Lou ◽  
Yong Sheng Zhang ◽  
Ze Xiang Li
Keyword(s):  
Genetic Algorithm ◽  
Kinematic Analysis ◽  
Parallel Manipulator ◽  
Pareto Front ◽  
Parallel Robot ◽  
Objective Functions ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Evolution Algorithm

The paper addresses the multi-objective optimization of a 2-DoF purely translational parallel manipulator. The kinematic analysis of the Proposed T2 parallel robot is introduced briefly. The objective functions are optimized simultaneously to improve Regular workspace Share (RWS) and Global Conditioning Index (GCI). A Multi-Objective Evolution Algorithm (MOEA) based on the Control Elitist Non-dominated Sorting Genetic Algorithm (controlled ENSGA-II) is used to find the Pareto front. The optimization results show that this method is efficient. The parallel manipulator prototype is also exhibited here.

scholarly journals Comparison of Planar Parallel Manipulator Architectures Based on a Multi-Objective Design Optimization Approach

2010 ◽  
Author(s):  
Damien Chablat ◽  
Ste´phane Caro ◽  
Raza Ur-Rehman ◽  
Philippe Wenger
Keyword(s):  
Genetic Algorithm ◽  
Design Optimization ◽  
Parallel Manipulator ◽  
Optimization Problem ◽  
Optimization Approach ◽  
Objective Functions ◽  
Multi Objective ◽  
Planar Parallel Manipulator ◽  
Moving Platform ◽  
Pareto Frontiers

This paper deals with the comparison of planar parallel manipulator architectures based on a multi-objective design optimization approach. The manipulator architectures are compared with regard to their mass in motion and their regular workspace size, i.e., the objective functions. The optimization problem is subject to constraints on the manipulator dexterity and stiffness. For a given external wrench, the displacements of the moving platform have to be smaller than given values throughout the obtained maximum regular dexterous workspace. The contributions of the paper are highlighted with the study of 3-PRR, 3-RPR and 3-RRR planar parallel manipulator architectures, which are compared by means of their Pareto frontiers obtained with a genetic algorithm.

Parallel Micro Manipulator for Effective Optical Spot Array Alignment

2014 ◽  
Author(s):  
Zheng Yuan Li ◽  
Sae Whan Park ◽  
Yong Seok Inh ◽  
Jong Yoon Choi ◽  
Ja Choon Koo
Keyword(s):  
Genetic Algorithm ◽  
Parallel Manipulator ◽  
Experimental Result ◽  
Kinematic Characteristic ◽  
Maskless Lithography ◽  
Nano Fabrication ◽  
Micro Manipulator ◽  
Spot Array ◽  
Exposure Process ◽  
Lithography Technology

Photolithography is one of the core technologies of micro-nano fabrication. Recently, lithography technology is applied to diverse field of technologies. These technologies include MEMS (micro electro mechanical system) devices, FPD (flat panel display), and semiconductor industry. When it comes to the typical exposure process of lithography technology, photomask costs is occupying large portion of the optical system. So, how to reduce the cost of the mask and employing maskless lithography technology has become an important issue to engineers. Although there being both advantages and disadvantages, maskless lithography is a receiving substantial attention from engineers in the fileds of micro-nano fabrication. With the development of technology, low cost, flexibility, efficiency in the fabrication of device are in high demand in maskless lithography technology. How to generate line/space patterns is gaining considerable attention in terms of maskless lithography exposure process. In order to achieve the accurate alignments of numerous optical heads within a reasonable amount of tack time, installing autonomous position align micro parallel manipulator system in each optical heads required. Applied parallel manipulator that consists of four 2-DOF (degree of freedom) decoupled actuator gives chances to provide 6-DOF independence motion, and has strength in high accuracy. It is thus, this parallel manipulator is suitable for the experiment. This paper covers the follows: First, we reported the DMD (Digital Micro mirror Device)-based makless lithography system to introduce spot array method in maskless digital exposure process. Second, applying a redundant parallel micro manipulator and analyzing kinematic characteristic of the 4-[PP]PS parallel manipulator is described. After that, comparing benefits and drawbacks of 4-[PP]PS parallel and 4-DOF serial manipulator is covered. Third, proposing a suitable error model of the system and applying the genetic algorithm to alignment spot array concerning position correction. Finally, we designed experiment which has vision sensor and align unit to verify positioning algorithm. Simulation and experimental result will be shown with the regard to parallel manipulator can find the optimal solution based on genetic algorithm and carry out the problem of spot array alignment by reducing the position error of the system.

scholarly journals Simulation and Optimisation of a Two Degree of Freedom, Planar, Parallel Manipulator

2021 ◽  
Author(s):  
◽  
Ben Haughey
Keyword(s):  
Genetic Algorithm ◽  
Simulation Model ◽  
Cycle Time ◽  
Parallel Manipulator ◽  
Robotic Manipulators ◽  
Degree Of Freedom ◽  
End Effector ◽  
Planar Parallel Manipulator ◽  
Pick And Place ◽  
Two Degree Of Freedom

<p>Development in pick-and-place robotic manipulators continues to grow as factory processes are streamlined. One configuration of these manipulators is the two degree of freedom, planar, parallel manipulator (2DOFPPM). A machine building company, RML Engineering Ltd., wishes to develop custom robotic manipulators that are optimised for individual pick-and-place applications. This thesis develops several tools to assist in the design process. The 2DOFPPM’s structure lends itself to fast and accurate translations in a single plane. However, the performance of the 2DOFPPM is highly dependent on its dimensions. The kinematics of the 2DOFPPM are explored and used to examine the reachable workspace of the manipulator. This method of analysis also gives insight into the relative speed and accuracy of the manipulator’s end-effector in the workspace. A simulation model of the 2DOFPPM has been developed in Matlab’s® SimMechanics®. This allows the detailed analysis of the manipulator’s dynamics. In order to provide meaningful input into the simulation model, a cubic spline trajectory planner is created. The algorithm uses an iterative approach of minimising the time between knots along the path, while ensuring the kinematic and dynamic limits of the motors and end-effector are abided by. The resulting trajectory can be considered near-minimum in terms of its cycle-time. The dimensions of the 2DOFPPM have a large effect on the performance of the manipulator. Four major dimensions are analysed to see the effect each has on the cycle-time over a standardised path. The dimensions are the proximal and distal arms, spacing of the motors and the height of the manipulator above the workspace. The solution space of all feasible combinations of these dimensions is produced revealing cycle-times with a large degree of variation over the same path. Several optimisation algorithms are applied to finding the manipulator configuration with the fastest cycle-time. A random restart hill-climber, stochastic hill-climber, simulated annealing and a genetic algorithm are developed. After each algorithm’s parameters are tuned, the genetic algorithm is shown to outperform the other techniques.</p>

Optimization of a Three Degrees of Freedom DELTA Manipulator for Well-Conditioned Workspace with a Floating Point Genetic Algorithm

2014 ◽  
Vol 4 (4) ◽  
pp. 1-14 ◽  
Author(s):  
Vitor Gaspar Silva ◽  
Mahmoud Tavakoli ◽  
Lino Marques
Keyword(s):  
Genetic Algorithm ◽  
Parallel Manipulator ◽  
Degrees Of Freedom ◽  
Condition Index ◽  
Global Search ◽  
Search Method ◽  
Floating Point ◽  
Design Parameters ◽  
Global Condition ◽  
Three Degrees Of Freedom

This paper demonstrates dexterity optimization of a three degrees of freedom (3 DOF) Delta manipulator. The parallel manipulator consists of three identical chains and is able to move on all three translational axes. In order to optimize the manipulator in term of dexterity, a floating point Genetic Algorithm (GA) global search method was applied. This algorithm intends to maximize the Global Condition Index (GCI) of the manipulator over its workspace and to propose the best design parameters such as the length of the links which result in a higher GCI and thus a better dexterity.

scholarly journals Simulation and Optimisation of a Two Degree of Freedom, Planar, Parallel Manipulator

2021 ◽  
Author(s):  
◽  
Ben Haughey
Keyword(s):  
Genetic Algorithm ◽  
Simulation Model ◽  
Cycle Time ◽  
Parallel Manipulator ◽  
Robotic Manipulators ◽  
Degree Of Freedom ◽  
End Effector ◽  
Planar Parallel Manipulator ◽  
Pick And Place ◽  
Two Degree Of Freedom

<p>Development in pick-and-place robotic manipulators continues to grow as factory processes are streamlined. One configuration of these manipulators is the two degree of freedom, planar, parallel manipulator (2DOFPPM). A machine building company, RML Engineering Ltd., wishes to develop custom robotic manipulators that are optimised for individual pick-and-place applications. This thesis develops several tools to assist in the design process. The 2DOFPPM’s structure lends itself to fast and accurate translations in a single plane. However, the performance of the 2DOFPPM is highly dependent on its dimensions. The kinematics of the 2DOFPPM are explored and used to examine the reachable workspace of the manipulator. This method of analysis also gives insight into the relative speed and accuracy of the manipulator’s end-effector in the workspace. A simulation model of the 2DOFPPM has been developed in Matlab’s® SimMechanics®. This allows the detailed analysis of the manipulator’s dynamics. In order to provide meaningful input into the simulation model, a cubic spline trajectory planner is created. The algorithm uses an iterative approach of minimising the time between knots along the path, while ensuring the kinematic and dynamic limits of the motors and end-effector are abided by. The resulting trajectory can be considered near-minimum in terms of its cycle-time. The dimensions of the 2DOFPPM have a large effect on the performance of the manipulator. Four major dimensions are analysed to see the effect each has on the cycle-time over a standardised path. The dimensions are the proximal and distal arms, spacing of the motors and the height of the manipulator above the workspace. The solution space of all feasible combinations of these dimensions is produced revealing cycle-times with a large degree of variation over the same path. Several optimisation algorithms are applied to finding the manipulator configuration with the fastest cycle-time. A random restart hill-climber, stochastic hill-climber, simulated annealing and a genetic algorithm are developed. After each algorithm’s parameters are tuned, the genetic algorithm is shown to outperform the other techniques.</p>

The ground state energy of the ±J spin glass from the genetic algorithm

1994 ◽  
Vol 4 (9) ◽  
pp. 1281-1285 ◽  
Author(s):  
P. Sutton ◽  
D. L. Hunter ◽  
N. Jan
Keyword(s):  
Genetic Algorithm ◽  
Spin Glass ◽  
Ground State Energy ◽  
Ground State ◽  
State Energy
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