Optimization on robot arm machining by using genetic algorithms

Abstract

In this study, an optimization problem on the robot arm machining is formulated and solved by using genetic algorithms (GAs). The proposed approach adopts direct kinematics model and utilizes GA's global search ability to find the optimum solution. The direct kinematics equations of the robot arm are formulated and can be used to compute the endeffector coordinates. Based on these, the objective of optimum machining along a set of points can be evolutionarily evaluated with the distance between machining points and end-effector positions. Besides, a 3D CAD application, CATIA, is used to build up the 3D models of the robot arm, work-pieces and their components. A simulated experiment in CATIA is used to verify the computation results first and a practical control on the robot arm through the RS232 port is also performed. From the results, this approach is proved to be robust and can be suitable for most machining needs when robot arms are adopted as the machining tools.

Proposta de algoritmo otimizador de caminhos para manipuladores robóticos em ambientes com presença de obstáculos

“…O algoritmo genético (AG) é o método mais famoso, e é abordado em algumas etapas do presente trabalho. Ele é utilizado pela maioria dos autores citados neste capítulo, como Toogood, Hao e Wong (1995), Jiang, Yao e Zhou (2018), Kazem, Mahdi e Oudah (2008), Yue et al (2002) e Liu, Chen e Tsai (2007).…”

“…A minimização de erro de posição é o mais simples dos objetivos a serem alcançados para manipuladores em ambientes 3D. Liu, Chen e Tsai (2007) propõem a utilização de AG para otimizar o erro de posição com um menor deslocamento das juntas.…”