Parallel-Populations Genetic Algorithm for the Optimization of Cubic Polynomial Joint Trajectories for Industrial Robots

2011 ◽  
pp. 83-92 ◽  
Author(s):  
Fares J. Abu-Dakka ◽  
Iyad F. Assad ◽  
Francisco Valero ◽  
Vicente Mata
Keyword(s):  
Genetic Algorithm ◽  
Industrial Robots ◽  
Cubic Polynomial

VIBRATION OPTIMIZATION OF A PASSIVE SUSPENSION SYSTEM VIA GENETIC ALGORITHM

2012 ◽  
Vol 04 (01) ◽  
pp. 1250022 ◽  
Author(s):  
S. D. JABEEN
Keyword(s):  
Genetic Algorithm ◽  
Center Of Mass ◽  
Suspension System ◽  
Design Parameters ◽  
Suspension Spring ◽  
Real Coded Genetic Algorithm ◽  
Cubic Polynomial ◽  
Passive Suspension System ◽  
Technological Constraints ◽  
Iso 2631

In this paper, we have formulated mathematical models to optimize the bouncing transmissibility of the sprung mass of the half car system with passengers' seat suspensions considering different road conditions. The corresponding problem has been solved with the help of advanced real coded Genetic Algorithm (GA). The nonlinearity of suspension spring and damper, which are the most important characteristics of the suspension, has been taken into account in order to validate the model to real applications. The nonlinear cubic polynomial has been used to describe the spring characteristic and a quadratic polynomial has been used to describe the damper characteristic. The coefficients of each polynomial represent the design parameters of the suspension system and are to be determined. To find these parameters we have formulated a nonlinear optimization problem in which the bouncing transmissibility of the sprung mass at the center of mass has been minimized with respect to technological constraints and the constraints which satisfy the performance as per ISO 2631 standards. The advanced real coded GA has been used to solve this problem in time domain and the results obtained have been compared to those obtained using the existing design parameters. The objective function and the constraints have been evaluated by simulating the vehicle model over two roads with multiple bumps at uniform velocity.

scholarly journals Fixed Task Scheduling of Industrial Robot using Genetic Algorithm Based Travelling Salesman Problem

2020 ◽  
Vol 9 (5) ◽  
pp. 1771-1775
Keyword(s):  
Genetic Algorithm ◽  
Task Scheduling ◽  
Shortest Path ◽  
Completion Time ◽  
Travelling Salesman Problem ◽  
Industrial Robots ◽  
Scheduling Problem ◽  
Search Technique ◽  
Travelling Salesman ◽  
Algorithm Search

The task scheduling of any industrial robots is a prior requirement to effectively use the capability by obtaining shortest path with optimum completion time. In this article, we have presented Travelling Salesman Problem (TSP) with Genetic Algorithm (GA) search technique based task scheduling technique for obtaining optimum shortest path of the task.TSP finds an optimal solution to search for the shortest route by considering every location for completing the required tasks by setting up GA. This article embrace the adaption and implementation of the Genetic Algorithm search strategy for the task scheduling problem in the cooperative control of multiple resources for getting shortest path with minimize the completion time for two zone specific task allocation problem. It can be inferred from the simulation results that the Genetic Algorithm search technique can be considered as a viable solution for the task scheduling problem.

scholarly journals DESIGNING HEDGE ALGEBRAIC CONTROLLER AND OPTIMIZING BY GENETIC ALGORITHM FOR SERIAL ROBOTS ADHERING TRAJECTORIES

2020 ◽  
Vol 36 (3) ◽  
pp. 265-283
Author(s):  
Nguyen Tien Duy ◽  
Vu Duc Vuong
Keyword(s):  
Genetic Algorithm ◽  
Industrial Revolution ◽  
Industrial Robots ◽  
Rule Base ◽  
Base System ◽  
Robot Arm ◽  
Linguistic Rule ◽  
Serial Robots ◽  
Simulation Results ◽  
Fuzzy Parameters

In recent years, the application of hedge algebras in the field of control has been studied. The results show that this approach has many advantages. In additions, industrial robots are being well-developed and extensively used, especially in the industrial revolution 4.0. Accurate control of industrial robots is a class of problems that many scientists are interested in. In this paper, we design a controller based on hedge algebra for serial robots. The control rule is given by linguistic rule base system. The goal is to accurately control the moving robot arm which adheres given trajectories. Optimization of fuzzy parameters for the controller is done by genetic algorithms. The system has been simulated on the Matlab-Simulink software. The simulation results show that the orbital deviation is very small. Moreover, the controller worked well with correct control quality. This result once presents the simplicity and efficiency of the hedge algebras approach to control.

scholarly journals Genetic Optimization of a Manipulator: Comparison between Straight, Rounded, and Curved Mechanism Links

2021 ◽  
Vol 11 (6) ◽  
pp. 2471
Author(s):  
Robert Pastor ◽  
Zdenko Bobovský ◽  
Daniel Huczala ◽  
Stefan Grushko
Keyword(s):  
Genetic Algorithm ◽  
Optimization Algorithm ◽  
Lower Cost ◽  
Robot Manipulators ◽  
Industrial Robots ◽  
Genetic Optimization ◽  
Mechanism Synthesis ◽  
Angular Structure ◽  
Manipulator Link ◽  
Hermite Spline

There are several ubiquitous kinematic structures that are used in industrial robots, with the most prominent being a six-axis angular structure. However, researchers are experimenting with task-based mechanism synthesis that could provide higher efficiency with custom optimized manipulators. Many studies have focused on finding the most efficient optimization algorithm for task-based robot manipulators. These manipulators, however, are usually optimized from simple modular joints and links, without exploring more elaborate modules. Here, we show that link modules defined by small numbers of parameters have better performance than more complicated ones. We compare four different manipulator link types, namely basic predefined links with fixed dimensions, straight links that can be optimized for different lengths, rounded links, and links with a curvature defined by a Hermite spline. Manipulators are then built from these modules using a genetic algorithm and are optimized for three different tasks. The results demonstrate that manipulators built from simple links not only converge faster, which is expected given the fewer optimized parameters, but also converge on lower cost values.

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