Adaptive motion pattern generation on balancing of humanoid robot movement

Azhar Aulia Saputra; Achmad Subhan Khalilullah; Indra Adji Sulistijono; Naoyuki Kubota

doi:10.1109/CCECE.2015.7129499

Adaptive motion pattern generation on balancing of humanoid robot movement

Azhar Aulia Saputra, Achmad Subhan Khalilullah, Indra Adji Sulistijono, Naoyuki Kubota

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

14 Scopus citations

Abstract

This paper discusses about adaptive trajectory control applied in motion pattern trajectory of humanoid robot movement. The aim of this research is to increase the stabilization of robot during walking and running. In this research, the control system produced the next step of the trajectory based on the current condition and analyzed the center of gravity point from the body of the robot. According to this, robot posed the foot step depend on the location of center of gravity point and stop the swing of its foot when the foot has reached the ground. In order to reduce the vibration effect arised by the swing of robot steps, this system is supported by vibration control. Robot is also supported by hand reaction learning system based on recurrent neural network. The trajectory pattern of robot movement has 2 trajectory equations: ankle trajectory formed by circle function in Cartesian coordinate space and pelvis trajectory formed by the third order polynomial equation. Both of them are influenced by inclination of the body of robot. We used the inverted pendulum approach combined with dynamic step trajectory. By using this system, robot can walk in the different surface and uneven surface. This system is applied on humanoid robot EROS (EEPIS Robot Soccer).

Original language	English
Title of host publication	2015 IEEE 28th Canadian Conference on Electrical and Computer Engineering, CCECE 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1479-1484
Number of pages	6
Edition	June
ISBN (Electronic)	9781479958276
DOIs	https://doi.org/10.1109/CCECE.2015.7129499
State	Published - 19 Jun 2015
Externally published	Yes

Publication series

Name	Canadian Conference on Electrical and Computer Engineering
Number	June
Volume	2015-June
ISSN (Print)	0840-7789

Bibliographical note

Publisher Copyright:
© 2015 IEEE.

Keywords

Adaptive trajectory
center of gravity
inverted pendulum

ASJC Scopus subject areas

Hardware and Architecture
Electrical and Electronic Engineering

Access to Document

10.1109/CCECE.2015.7129499

Cite this

Saputra, A. A., Khalilullah, A. S., Sulistijono, I. A., & Kubota, N. (2015). Adaptive motion pattern generation on balancing of humanoid robot movement. In 2015 IEEE 28th Canadian Conference on Electrical and Computer Engineering, CCECE 2015 (June ed., pp. 1479-1484). Article 7129499 (Canadian Conference on Electrical and Computer Engineering; Vol. 2015-June, No. June). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CCECE.2015.7129499

Saputra, Azhar Aulia ; Khalilullah, Achmad Subhan ; Sulistijono, Indra Adji et al. / Adaptive motion pattern generation on balancing of humanoid robot movement. 2015 IEEE 28th Canadian Conference on Electrical and Computer Engineering, CCECE 2015. June. ed. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 1479-1484 (Canadian Conference on Electrical and Computer Engineering; June).

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title = "Adaptive motion pattern generation on balancing of humanoid robot movement",

abstract = "This paper discusses about adaptive trajectory control applied in motion pattern trajectory of humanoid robot movement. The aim of this research is to increase the stabilization of robot during walking and running. In this research, the control system produced the next step of the trajectory based on the current condition and analyzed the center of gravity point from the body of the robot. According to this, robot posed the foot step depend on the location of center of gravity point and stop the swing of its foot when the foot has reached the ground. In order to reduce the vibration effect arised by the swing of robot steps, this system is supported by vibration control. Robot is also supported by hand reaction learning system based on recurrent neural network. The trajectory pattern of robot movement has 2 trajectory equations: ankle trajectory formed by circle function in Cartesian coordinate space and pelvis trajectory formed by the third order polynomial equation. Both of them are influenced by inclination of the body of robot. We used the inverted pendulum approach combined with dynamic step trajectory. By using this system, robot can walk in the different surface and uneven surface. This system is applied on humanoid robot EROS (EEPIS Robot Soccer).",

keywords = "Adaptive trajectory, center of gravity, inverted pendulum",

author = "Saputra, \{Azhar Aulia\} and Khalilullah, \{Achmad Subhan\} and Sulistijono, \{Indra Adji\} and Naoyuki Kubota",

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year = "2015",

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doi = "10.1109/CCECE.2015.7129499",

language = "English",

series = "Canadian Conference on Electrical and Computer Engineering",

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Saputra, AA, Khalilullah, AS, Sulistijono, IA & Kubota, N 2015, Adaptive motion pattern generation on balancing of humanoid robot movement. in 2015 IEEE 28th Canadian Conference on Electrical and Computer Engineering, CCECE 2015. June edn, 7129499, Canadian Conference on Electrical and Computer Engineering, no. June, vol. 2015-June, Institute of Electrical and Electronics Engineers Inc., pp. 1479-1484. https://doi.org/10.1109/CCECE.2015.7129499

Adaptive motion pattern generation on balancing of humanoid robot movement. / Saputra, Azhar Aulia; Khalilullah, Achmad Subhan; Sulistijono, Indra Adji et al.
2015 IEEE 28th Canadian Conference on Electrical and Computer Engineering, CCECE 2015. June. ed. Institute of Electrical and Electronics Engineers Inc., 2015. p. 1479-1484 7129499 (Canadian Conference on Electrical and Computer Engineering; Vol. 2015-June, No. June).

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

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AU - Khalilullah, Achmad Subhan

AU - Sulistijono, Indra Adji

AU - Kubota, Naoyuki

PY - 2015/6/19

Y1 - 2015/6/19

N2 - This paper discusses about adaptive trajectory control applied in motion pattern trajectory of humanoid robot movement. The aim of this research is to increase the stabilization of robot during walking and running. In this research, the control system produced the next step of the trajectory based on the current condition and analyzed the center of gravity point from the body of the robot. According to this, robot posed the foot step depend on the location of center of gravity point and stop the swing of its foot when the foot has reached the ground. In order to reduce the vibration effect arised by the swing of robot steps, this system is supported by vibration control. Robot is also supported by hand reaction learning system based on recurrent neural network. The trajectory pattern of robot movement has 2 trajectory equations: ankle trajectory formed by circle function in Cartesian coordinate space and pelvis trajectory formed by the third order polynomial equation. Both of them are influenced by inclination of the body of robot. We used the inverted pendulum approach combined with dynamic step trajectory. By using this system, robot can walk in the different surface and uneven surface. This system is applied on humanoid robot EROS (EEPIS Robot Soccer).

AB - This paper discusses about adaptive trajectory control applied in motion pattern trajectory of humanoid robot movement. The aim of this research is to increase the stabilization of robot during walking and running. In this research, the control system produced the next step of the trajectory based on the current condition and analyzed the center of gravity point from the body of the robot. According to this, robot posed the foot step depend on the location of center of gravity point and stop the swing of its foot when the foot has reached the ground. In order to reduce the vibration effect arised by the swing of robot steps, this system is supported by vibration control. Robot is also supported by hand reaction learning system based on recurrent neural network. The trajectory pattern of robot movement has 2 trajectory equations: ankle trajectory formed by circle function in Cartesian coordinate space and pelvis trajectory formed by the third order polynomial equation. Both of them are influenced by inclination of the body of robot. We used the inverted pendulum approach combined with dynamic step trajectory. By using this system, robot can walk in the different surface and uneven surface. This system is applied on humanoid robot EROS (EEPIS Robot Soccer).

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PB - Institute of Electrical and Electronics Engineers Inc.

ER -

Saputra AA, Khalilullah AS, Sulistijono IA, Kubota N. Adaptive motion pattern generation on balancing of humanoid robot movement. In 2015 IEEE 28th Canadian Conference on Electrical and Computer Engineering, CCECE 2015. June ed. Institute of Electrical and Electronics Engineers Inc. 2015. p. 1479-1484. 7129499. (Canadian Conference on Electrical and Computer Engineering; June). doi: 10.1109/CCECE.2015.7129499

Adaptive motion pattern generation on balancing of humanoid robot movement

Abstract

Publication series

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this