Error optimization using Bat and PSO algorithms for machine vision system based tool movement

Author

Garg, Adesh ; Mahapatra, Prasant Kumar ; Kumar, Ajit

Author_Institution

Biomed. Instrum. Div., Central Sci. Instrum. Organ., Chandigarh, India

fYear

2014

fDate

24-27 Sept. 2014

Firstpage

2689

Lastpage

2693

Abstract

This paper presents a comparison of Bat and Particle Swarm Optimization (PSO) algorithms for optimization of lathe tool positional error in a developed machine vision system for determination of lathe tool position and verification. Bat algorithm is based on echolocation behavior of bats while PSO is inspired by social behavior of birds flocking in search for food. Both metaheuristic algorithms were tested on lathe tool movement ranging from 0.020 mm to 7 mm. The results for various lathe tool movements have demonstrated that Bat algorithm outperforms the PSO algorithm.

Keywords

computer vision; lathes; particle swarm optimisation; production engineering computing; Bat algorithm; PSO algorithm; echolocation behavior; error optimization; lathe tool position; lathe tool positional error; lathe tool verification; machine vision system; metaheuristic algorithm; particle swarm optimization; tool movement; Algorithm design and analysis; Approximation algorithms; Informatics; Machine vision; Machining; Optimization; Particle swarm optimization; Bat Algorithm; Bio-inspired Algorithms; Error optimization; Machine Vision System; PSO Algorithm;

fLanguage

English

Publisher

ieee

Conference_Titel

Advances in Computing, Communications and Informatics (ICACCI, 2014 International Conference on

Conference_Location

New Delhi

Print_ISBN

978-1-4799-3078-4

Type

conf

DOI

10.1109/ICACCI.2014.6968298

Filename

6968298