Efficiency energy on humanoid robot walking using evolutionary algorithm

Azhar Aulia Saputra; Takahiro Takeda; Naoyuki Kubota

doi:10.1109/CEC.2015.7256941

Efficiency energy on humanoid robot walking using evolutionary algorithm

Azhar Aulia Saputra, Takahiro Takeda, Naoyuki Kubota

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

16 Scopus citations

Abstract

One of the problems in humanoid locomotion generation is energy efficiency. This paper proposes a method for energy efficiency optimization in simple humanoid robot locomotion using single objective genetic algorithm. With the aim to produce walking trajectory system using minimum energy and good stabilization, torque and oscillation analysis are required to calculate the stabilization. The number of desired outputs in this system is 4 parameters and the number of inputs is 9 parameters. We used neural network with back propagation learning mechanism to realize the relationship between input and output data as well as producing fitness function for genetic algorithm. The trajectory system has 2 trajectory equations, which is pelvis trajectory and ankle trajectory. Ankle trajectory is formed from circle function in Cartesian coordinate space and pelvis trajectory is formed from third order polynomial equation. Both of them are influenced by inclination of robot body. In the experiment, we apply this system using Bioloid robot with inertial sensor already installed. The experimental results show the analysis of energy by observing the torque resulted by servomotor in each joint. We observe that using this system, the torque value resulted by servomotors was decreased and has good stabilization.

Original language	English
Title of host publication	2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	573-578
Number of pages	6
ISBN (Electronic)	9781479974924
DOIs	https://doi.org/10.1109/CEC.2015.7256941
State	Published - 10 Sep 2015
Externally published	Yes
Event	IEEE Congress on Evolutionary Computation, CEC 2015 - Sendai, Japan Duration: 25 May 2015 → 28 May 2015

Publication series

Name	2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings

Conference

Conference	IEEE Congress on Evolutionary Computation, CEC 2015
Country/Territory	Japan
City	Sendai
Period	25/05/15 → 28/05/15

Bibliographical note

Publisher Copyright:
© 2015 IEEE.

Keywords

Bioloid
Efficiency energy
Neural Network
SSGA
Trajectory Generation

ASJC Scopus subject areas

Computer Science Applications
Computational Mathematics

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/CEC.2015.7256941

Cite this

Saputra, A. A., Takeda, T., & Kubota, N. (2015). Efficiency energy on humanoid robot walking using evolutionary algorithm. In 2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings (pp. 573-578). Article 7256941 (2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CEC.2015.7256941

@inproceedings{a352e0a754794647a74bff9cea41c534,

title = "Efficiency energy on humanoid robot walking using evolutionary algorithm",

abstract = "One of the problems in humanoid locomotion generation is energy efficiency. This paper proposes a method for energy efficiency optimization in simple humanoid robot locomotion using single objective genetic algorithm. With the aim to produce walking trajectory system using minimum energy and good stabilization, torque and oscillation analysis are required to calculate the stabilization. The number of desired outputs in this system is 4 parameters and the number of inputs is 9 parameters. We used neural network with back propagation learning mechanism to realize the relationship between input and output data as well as producing fitness function for genetic algorithm. The trajectory system has 2 trajectory equations, which is pelvis trajectory and ankle trajectory. Ankle trajectory is formed from circle function in Cartesian coordinate space and pelvis trajectory is formed from third order polynomial equation. Both of them are influenced by inclination of robot body. In the experiment, we apply this system using Bioloid robot with inertial sensor already installed. The experimental results show the analysis of energy by observing the torque resulted by servomotor in each joint. We observe that using this system, the torque value resulted by servomotors was decreased and has good stabilization.",

keywords = "Bioloid, Efficiency energy, Neural Network, SSGA, Trajectory Generation",

author = "Saputra, \{Azhar Aulia\} and Takahiro Takeda and Naoyuki Kubota",

note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; IEEE Congress on Evolutionary Computation, CEC 2015 ; Conference date: 25-05-2015 Through 28-05-2015",

year = "2015",

month = sep,

day = "10",

doi = "10.1109/CEC.2015.7256941",

language = "English",

series = "2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "573--578",

booktitle = "2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings",

address = "United States",

}

Saputra, AA, Takeda, T & Kubota, N 2015, Efficiency energy on humanoid robot walking using evolutionary algorithm. in 2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings., 7256941, 2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 573-578, IEEE Congress on Evolutionary Computation, CEC 2015, Sendai, Japan, 25/05/15. https://doi.org/10.1109/CEC.2015.7256941

Efficiency energy on humanoid robot walking using evolutionary algorithm. / Saputra, Azhar Aulia; Takeda, Takahiro; Kubota, Naoyuki.
2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2015. p. 573-578 7256941 (2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Efficiency energy on humanoid robot walking using evolutionary algorithm

AU - Saputra, Azhar Aulia

AU - Takeda, Takahiro

AU - Kubota, Naoyuki

PY - 2015/9/10

Y1 - 2015/9/10

N2 - One of the problems in humanoid locomotion generation is energy efficiency. This paper proposes a method for energy efficiency optimization in simple humanoid robot locomotion using single objective genetic algorithm. With the aim to produce walking trajectory system using minimum energy and good stabilization, torque and oscillation analysis are required to calculate the stabilization. The number of desired outputs in this system is 4 parameters and the number of inputs is 9 parameters. We used neural network with back propagation learning mechanism to realize the relationship between input and output data as well as producing fitness function for genetic algorithm. The trajectory system has 2 trajectory equations, which is pelvis trajectory and ankle trajectory. Ankle trajectory is formed from circle function in Cartesian coordinate space and pelvis trajectory is formed from third order polynomial equation. Both of them are influenced by inclination of robot body. In the experiment, we apply this system using Bioloid robot with inertial sensor already installed. The experimental results show the analysis of energy by observing the torque resulted by servomotor in each joint. We observe that using this system, the torque value resulted by servomotors was decreased and has good stabilization.

AB - One of the problems in humanoid locomotion generation is energy efficiency. This paper proposes a method for energy efficiency optimization in simple humanoid robot locomotion using single objective genetic algorithm. With the aim to produce walking trajectory system using minimum energy and good stabilization, torque and oscillation analysis are required to calculate the stabilization. The number of desired outputs in this system is 4 parameters and the number of inputs is 9 parameters. We used neural network with back propagation learning mechanism to realize the relationship between input and output data as well as producing fitness function for genetic algorithm. The trajectory system has 2 trajectory equations, which is pelvis trajectory and ankle trajectory. Ankle trajectory is formed from circle function in Cartesian coordinate space and pelvis trajectory is formed from third order polynomial equation. Both of them are influenced by inclination of robot body. In the experiment, we apply this system using Bioloid robot with inertial sensor already installed. The experimental results show the analysis of energy by observing the torque resulted by servomotor in each joint. We observe that using this system, the torque value resulted by servomotors was decreased and has good stabilization.

KW - Bioloid

KW - Efficiency energy

KW - Neural Network

KW - SSGA

KW - Trajectory Generation

UR - https://www.scopus.com/pages/publications/84958080351

U2 - 10.1109/CEC.2015.7256941

DO - 10.1109/CEC.2015.7256941

M3 - Conference contribution

AN - SCOPUS:84958080351

T3 - 2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings

SP - 573

EP - 578

BT - 2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - IEEE Congress on Evolutionary Computation, CEC 2015

Y2 - 25 May 2015 through 28 May 2015

ER -

Efficiency energy on humanoid robot walking using evolutionary algorithm

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

UN SDGs

Access to Document

Fingerprint

Cite this