Open AccessAssistive Robot Simulator for Multi-Objective Evolutionary Algorithm Application
Author(s) -
Zulkifli Mohamed,
Muhammad Azmi Ayub,
Mohd Hanif Mohd Ramli,
Mohd Saiful Bahari Shaari,
S. Khusairi
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i4.27.22506
Subject(s) - simulation , robot , computer science , kinematics , mechatronics , multi objective optimization , trajectory , task (project management) , engineering , artificial intelligence , physics , systems engineering , classical mechanics , astronomy , machine learning
This paper presents a new assistive robot simulator for multi-objective optimization application. The main function of the simulator is to simulate the trajectory of the robot arm when it moves from initial to a goal position in optimized manner. A multi-objective evolutionary algorithm (MOEA) is utilized to generate the robot arm motion optimizing three different objective function; optimum time, distance, and high stability. The generated neuron will be selected from the Pareto optimal based on the required objectives function. The robot will intelligently choose the best neuron for a specific task. For example, to move a glass of water required higher stability compare to move an empty mineral water bottle. The simulator will be connected to the real robot to test the performance in real environment. The kinematics, mechatronics and the real robot specification are utilized in the simulator. The performance of the simulator is presented in this paper.