Robust modeling of dynamic environment based on robot embodiment

Kuniaki Noda; Mototaka Suzuki; Naofumi Tsuchiya; Yuki Suga; Tetsuya Ogata; Shigeki Sugano

Robust modeling of dynamic environment based on robot embodiment

Kuniaki Noda^*, Mototaka Suzuki, Naofumi Tsuchiya, Yuki Suga, Tetsuya Ogata, Shigeki Sugano

^*Corresponding author for this work

Research output: Contribution to journal › Conference article › peer-review

6 Citations (Scopus)

Abstract

Recent studies on embodied cognitive science have shown us the possibility of emergence of more complex and nontrivial behaviors with quite simple designs if the designer takes the dynamics of the system-environment interaction into account properly. In this paper, we report our tentative classification experiments of several objects using the human-like autonomous robot, "WAMOEBA-2Ri". As modeling the environment, we focus on not only static aspects of the environment but also dynamic aspects of it including that of the system own. The visualized results of this experiment shows the integration of multimodal sensor dataset acquired by the system-environment interaction ("grasping") enable robust categorization of several objects. Finally, in discussion, we demonstrate a possible application to making "invariance in motion" emerge consequently by extending this approach.

Original language	English
Pages (from-to)	3565-3570
Number of pages	6
Journal	Proceedings - IEEE International Conference on Robotics and Automation
Volume	3
Publication status	Published - 2003 Dec 9
Event	2003 IEEE International Conference on Robotics and Automation - Taipei, Taiwan, Province of China Duration: 2003 Sept 14 → 2003 Sept 19

ASJC Scopus subject areas

Software
Control and Systems Engineering
Artificial Intelligence
Electrical and Electronic Engineering

Cite this

@article{d5f5f985311b49eba7c282d0a13b9a3d,

title = "Robust modeling of dynamic environment based on robot embodiment",

abstract = "Recent studies on embodied cognitive science have shown us the possibility of emergence of more complex and nontrivial behaviors with quite simple designs if the designer takes the dynamics of the system-environment interaction into account properly. In this paper, we report our tentative classification experiments of several objects using the human-like autonomous robot, {"}WAMOEBA-2Ri{"}. As modeling the environment, we focus on not only static aspects of the environment but also dynamic aspects of it including that of the system own. The visualized results of this experiment shows the integration of multimodal sensor dataset acquired by the system-environment interaction ({"}grasping{"}) enable robust categorization of several objects. Finally, in discussion, we demonstrate a possible application to making {"}invariance in motion{"} emerge consequently by extending this approach.",

author = "Kuniaki Noda and Mototaka Suzuki and Naofumi Tsuchiya and Yuki Suga and Tetsuya Ogata and Shigeki Sugano",

year = "2003",

month = dec,

day = "9",

language = "English",

volume = "3",

pages = "3565--3570",

journal = "Proceedings - IEEE International Conference on Robotics and Automation",

issn = "1050-4729",

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

note = "2003 IEEE International Conference on Robotics and Automation ; Conference date: 14-09-2003 Through 19-09-2003",

}

TY - JOUR

T1 - Robust modeling of dynamic environment based on robot embodiment

AU - Noda, Kuniaki

AU - Suzuki, Mototaka

AU - Tsuchiya, Naofumi

AU - Suga, Yuki

AU - Ogata, Tetsuya

AU - Sugano, Shigeki

PY - 2003/12/9

Y1 - 2003/12/9

N2 - Recent studies on embodied cognitive science have shown us the possibility of emergence of more complex and nontrivial behaviors with quite simple designs if the designer takes the dynamics of the system-environment interaction into account properly. In this paper, we report our tentative classification experiments of several objects using the human-like autonomous robot, "WAMOEBA-2Ri". As modeling the environment, we focus on not only static aspects of the environment but also dynamic aspects of it including that of the system own. The visualized results of this experiment shows the integration of multimodal sensor dataset acquired by the system-environment interaction ("grasping") enable robust categorization of several objects. Finally, in discussion, we demonstrate a possible application to making "invariance in motion" emerge consequently by extending this approach.

AB - Recent studies on embodied cognitive science have shown us the possibility of emergence of more complex and nontrivial behaviors with quite simple designs if the designer takes the dynamics of the system-environment interaction into account properly. In this paper, we report our tentative classification experiments of several objects using the human-like autonomous robot, "WAMOEBA-2Ri". As modeling the environment, we focus on not only static aspects of the environment but also dynamic aspects of it including that of the system own. The visualized results of this experiment shows the integration of multimodal sensor dataset acquired by the system-environment interaction ("grasping") enable robust categorization of several objects. Finally, in discussion, we demonstrate a possible application to making "invariance in motion" emerge consequently by extending this approach.

UR - http://www.scopus.com/inward/record.url?scp=0344464881&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0344464881&partnerID=8YFLogxK

M3 - Conference article

AN - SCOPUS:0344464881

SN - 1050-4729

VL - 3

SP - 3565

EP - 3570

JO - Proceedings - IEEE International Conference on Robotics and Automation

JF - Proceedings - IEEE International Conference on Robotics and Automation

T2 - 2003 IEEE International Conference on Robotics and Automation

Y2 - 14 September 2003 through 19 September 2003

ER -

Robust modeling of dynamic environment based on robot embodiment

Abstract

ASJC Scopus subject areas

Other files and links

Fingerprint

Cite this