Robots moving in formation by using neural network and radial basis functions

Kaoru Hirota; Tsuyoshi Kuwabara; Kenichi Ishida; Akihiko Miyanohara; Hiroaki Ohdachi; Toshihiro Ohsawa; Wataru Takeuchi; Naoyoshi Yubazaki; Masayuki Ohtani

Robots moving in formation by using neural network and radial basis functions

Kaoru Hirota^*, Tsuyoshi Kuwabara, Kenichi Ishida, Akihiko Miyanohara, Hiroaki Ohdachi, Toshihiro Ohsawa, Wataru Takeuchi, Naoyoshi Yubazaki, Masayuki Ohtani

^*Corresponding author for this work

Hosei University

Research output: Contribution to conference › Paper › peer-review

7 Citations (Scopus)

Abstract

Vision-based moving in formation by 4 mobile robots is presented. One robot who is a leader and goes first provides moving plans to the other robots who follow the leading robot. These robots perform to move in not only single line, but also triangular or diamond formation. Each robot detects the other robots by means of color image classification using three-layer neural network. In motion control, Radial Basis Function (RBF) network approximated by learning is used. In addition, hardware implementations and the results of demonstration how multiple mobile robots move in several formations are described.

Original language	English
Pages	91-94
Number of pages	4
Publication status	Published - 1995
Externally published	Yes
Event	Proceedings of the 1995 IEEE International Conference on Fuzzy Systems. Part 1 (of 5) - Yokohama, Jpn Duration: 20 Mar 1995 → 24 Mar 1995

Conference

Conference	Proceedings of the 1995 IEEE International Conference on Fuzzy Systems. Part 1 (of 5)
City	Yokohama, Jpn
Period	20/03/95 → 24/03/95

Cite this

@conference{5e8eb8d71b1946488b7b098dd33510a2,

title = "Robots moving in formation by using neural network and radial basis functions",

abstract = "Vision-based moving in formation by 4 mobile robots is presented. One robot who is a leader and goes first provides moving plans to the other robots who follow the leading robot. These robots perform to move in not only single line, but also triangular or diamond formation. Each robot detects the other robots by means of color image classification using three-layer neural network. In motion control, Radial Basis Function (RBF) network approximated by learning is used. In addition, hardware implementations and the results of demonstration how multiple mobile robots move in several formations are described.",

author = "Kaoru Hirota and Tsuyoshi Kuwabara and Kenichi Ishida and Akihiko Miyanohara and Hiroaki Ohdachi and Toshihiro Ohsawa and Wataru Takeuchi and Naoyoshi Yubazaki and Masayuki Ohtani",

year = "1995",

language = "English",

pages = "91--94",

note = "Proceedings of the 1995 IEEE International Conference on Fuzzy Systems. Part 1 (of 5) ; Conference date: 20-03-1995 Through 24-03-1995",

}

TY - CONF

T1 - Robots moving in formation by using neural network and radial basis functions

AU - Hirota, Kaoru

AU - Kuwabara, Tsuyoshi

AU - Ishida, Kenichi

AU - Miyanohara, Akihiko

AU - Ohdachi, Hiroaki

AU - Ohsawa, Toshihiro

AU - Takeuchi, Wataru

AU - Yubazaki, Naoyoshi

AU - Ohtani, Masayuki

PY - 1995

Y1 - 1995

N2 - Vision-based moving in formation by 4 mobile robots is presented. One robot who is a leader and goes first provides moving plans to the other robots who follow the leading robot. These robots perform to move in not only single line, but also triangular or diamond formation. Each robot detects the other robots by means of color image classification using three-layer neural network. In motion control, Radial Basis Function (RBF) network approximated by learning is used. In addition, hardware implementations and the results of demonstration how multiple mobile robots move in several formations are described.

AB - Vision-based moving in formation by 4 mobile robots is presented. One robot who is a leader and goes first provides moving plans to the other robots who follow the leading robot. These robots perform to move in not only single line, but also triangular or diamond formation. Each robot detects the other robots by means of color image classification using three-layer neural network. In motion control, Radial Basis Function (RBF) network approximated by learning is used. In addition, hardware implementations and the results of demonstration how multiple mobile robots move in several formations are described.

UR - http://www.scopus.com/inward/record.url?scp=0029215387&partnerID=8YFLogxK

M3 - Paper

AN - SCOPUS:0029215387

SP - 91

EP - 94

T2 - Proceedings of the 1995 IEEE International Conference on Fuzzy Systems. Part 1 (of 5)

Y2 - 20 March 1995 through 24 March 1995

ER -

Robots moving in formation by using neural network and radial basis functions

Abstract

Conference

Other files and links

Fingerprint

Cite this