General Information
    • ISSN: 1793-8201 (Print), 2972-4511 (Online)
    • Abbreviated Title: Int. J. Comput. Theory Eng.
    • Frequency: Quarterly
    • DOI: 10.7763/IJCTE
    • Editor-in-Chief: Prof. Mehmet Sahinoglu
    • Associate Editor-in-Chief: Assoc. Prof. Alberto Arteta, Assoc. Prof. Engin Maşazade
    • Managing Editor: Ms. Mia Hu
    • Abstracting/Indexing: Scopus (Since 2022), INSPEC (IET), CNKI,  Google Scholar, EBSCO, etc.
    • Average Days from Submission to Acceptance: 192 days
    • APC: 800 USD
    • E-mail:
    • Journal Metrics:
    • SCImago Journal & Country Rank
Prof. Mehmet Sahinoglu
Computer Science Department, Troy University, USA
I'm happy to take on the position of editor in chief of IJCTE. We encourage authors to submit papers concerning any branch of computer theory and engineering.

IJCTE 2015 Vol.7(2): 97-102 ISSN: 1793-8201
DOI: 10.7763/IJCTE.2015.V7.938

Converting Motion between Different Types of Humanoid Robots Using Genetic Algorithms

Mari Nishiyama and Hitoshi Iba

Abstract—The imitation between different types of robots remains an unsolved task for a long time. The assignment of the correct angles to each joint is critical for robot motion. However, different robots have different structures, thus this discrepancy causes a difficulty when converting a motion to another type of robot. For solving this problem, we propose a GA-based method that can find the conversion matrix needed to map joint angles of one robot to another. There are two objectives to consider when creating an imitation; reducing the difference between the ideal imitation and the converted imitation and keeping the stability. Three experiments were conducted; a stable experiment, an unstable experiment and a double learning experiment. As a result, the double experiment showed a high concordance rate of 93.5%, the highest stability and the fastest speed of all experiments. These results show great promise for the proposed method as a way to realize motion imitation between different types of robots.

Index Terms—Robot, imitation, motion planning, humanoid robot, genetic algorithms, autonomous learning.

Mari Nishiyama is with the Department of Electrical and Electronic Engineering, the University of Tokyo, Japan (e-mail: nishiyama@iba.t.utokyo.
Hitoshi Iba is with the Graduate School of Information Science and Technology, the University of Tokyo, Japan (e-mail: iba@iba.t.utokyo.


Cite: Mari Nishiyama and Hitoshi Iba, "Converting Motion between Different Types of Humanoid Robots Using Genetic Algorithms," International Journal of Computer Theory and Engineering vol. 7, no. 2, pp. 97-102, 2015.

Copyright © 2008-2024. International Association of Computer Science and Information Technology. All rights reserved.