A dual neural network for bi-criteria torque optimization of redundant robot manipulators

Shubao Liu; Jun Wang

doi:10.1007/978-3-540-30499-9_177

A dual neural network for bi-criteria torque optimization of redundant robot manipulators

Shubao Liu
, Jun Wang

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

7 Citations (Scopus)

Abstract

A dual neural network is presented for the bi-criteria joint torque optimization of kinematically redundant manipulators, which balances between the total energy consumption and the torque distribution among the joints. Joint torque limits are also incorporated simultaneously into the proposed optimization scheme. The dual neural network has a simple structure with only one layer of neurons and is proven to be globally exponentially convergent to the optimal solution. The effectiveness of dual neural network for this problem is demonstrated by simulation with the PUMA560 manipulator. © Springer-Verlag Berlin Heidelberg 2004.

Original language	English
Title of host publication	Neural Information Processing
Subtitle of host publication	11th International Conference, ICONIP 2004 Calcutta, India, November 22–25, 2004 Proceedings
Editors	Nikhil Ranjan Pal, Nik Kasabov, Rajani K. Mudi
Publisher	Springer
Pages	1142-1147
ISBN (Electronic)	978-3-540-30499-9
ISBN (Print)	978-3-540-23931-4
DOIs	https://doi.org/10.1007/978-3-540-30499-9_177
Publication status	Published - 2004
Externally published	Yes
Event	11th International Conference on Neural Information Processing (ICONIP 2004) - Calcutta, India Duration: 22 Nov 2004 → 25 Nov 2004

Publication series

Name	Lecture Notes in Computer Science
Volume	3316
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	11th International Conference on Neural Information Processing (ICONIP 2004)
Place	India
City	Calcutta
Period	22/11/04 → 25/11/04

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10.1007/978-3-540-30499-9_177

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Liu, S., & Wang, J. (2004). A dual neural network for bi-criteria torque optimization of redundant robot manipulators. In N. R. Pal, N. Kasabov, & R. K. Mudi (Eds.), Neural Information Processing: 11th International Conference, ICONIP 2004 Calcutta, India, November 22–25, 2004 Proceedings (pp. 1142-1147). (Lecture Notes in Computer Science; Vol. 3316). Springer . https://doi.org/10.1007/978-3-540-30499-9_177

Liu, Shubao ; Wang, Jun. / A dual neural network for bi-criteria torque optimization of redundant robot manipulators. Neural Information Processing: 11th International Conference, ICONIP 2004 Calcutta, India, November 22–25, 2004 Proceedings. editor / Nikhil Ranjan Pal ; Nik Kasabov ; Rajani K. Mudi. Springer , 2004. pp. 1142-1147 (Lecture Notes in Computer Science).

@inproceedings{1c8c723a039048998f8be6af4dd9678b,

title = "A dual neural network for bi-criteria torque optimization of redundant robot manipulators",

abstract = "A dual neural network is presented for the bi-criteria joint torque optimization of kinematically redundant manipulators, which balances between the total energy consumption and the torque distribution among the joints. Joint torque limits are also incorporated simultaneously into the proposed optimization scheme. The dual neural network has a simple structure with only one layer of neurons and is proven to be globally exponentially convergent to the optimal solution. The effectiveness of dual neural network for this problem is demonstrated by simulation with the PUMA560 manipulator. {\textcopyright} Springer-Verlag Berlin Heidelberg 2004.",

author = "Shubao Liu and Jun Wang",

year = "2004",

doi = "10.1007/978-3-540-30499-9\_177",

language = "English",

isbn = "978-3-540-23931-4",

series = "Lecture Notes in Computer Science",

publisher = "Springer ",

pages = "1142--1147",

editor = "Pal, \{Nikhil Ranjan\} and Nik Kasabov and Mudi, \{Rajani K.\}",

booktitle = "Neural Information Processing",

note = "11th International Conference on Neural Information Processing (ICONIP 2004) ; Conference date: 22-11-2004 Through 25-11-2004",

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Liu, S & Wang, J 2004, A dual neural network for bi-criteria torque optimization of redundant robot manipulators. in NR Pal, N Kasabov & RK Mudi (eds), Neural Information Processing: 11th International Conference, ICONIP 2004 Calcutta, India, November 22–25, 2004 Proceedings. Lecture Notes in Computer Science, vol. 3316, Springer , pp. 1142-1147, 11th International Conference on Neural Information Processing (ICONIP 2004), Calcutta, India, 22/11/04. https://doi.org/10.1007/978-3-540-30499-9_177

A dual neural network for bi-criteria torque optimization of redundant robot manipulators. / Liu, Shubao; Wang, Jun.
Neural Information Processing: 11th International Conference, ICONIP 2004 Calcutta, India, November 22–25, 2004 Proceedings. ed. / Nikhil Ranjan Pal; Nik Kasabov; Rajani K. Mudi. Springer , 2004. p. 1142-1147 (Lecture Notes in Computer Science; Vol. 3316).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

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AU - Liu, Shubao

AU - Wang, Jun

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N2 - A dual neural network is presented for the bi-criteria joint torque optimization of kinematically redundant manipulators, which balances between the total energy consumption and the torque distribution among the joints. Joint torque limits are also incorporated simultaneously into the proposed optimization scheme. The dual neural network has a simple structure with only one layer of neurons and is proven to be globally exponentially convergent to the optimal solution. The effectiveness of dual neural network for this problem is demonstrated by simulation with the PUMA560 manipulator. © Springer-Verlag Berlin Heidelberg 2004.

AB - A dual neural network is presented for the bi-criteria joint torque optimization of kinematically redundant manipulators, which balances between the total energy consumption and the torque distribution among the joints. Joint torque limits are also incorporated simultaneously into the proposed optimization scheme. The dual neural network has a simple structure with only one layer of neurons and is proven to be globally exponentially convergent to the optimal solution. The effectiveness of dual neural network for this problem is demonstrated by simulation with the PUMA560 manipulator. © Springer-Verlag Berlin Heidelberg 2004.

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DO - 10.1007/978-3-540-30499-9_177

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 978-3-540-23931-4

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BT - Neural Information Processing

A2 - Pal, Nikhil Ranjan

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Liu S, Wang J. A dual neural network for bi-criteria torque optimization of redundant robot manipulators. In Pal NR, Kasabov N, Mudi RK, editors, Neural Information Processing: 11th International Conference, ICONIP 2004 Calcutta, India, November 22–25, 2004 Proceedings. Springer . 2004. p. 1142-1147. (Lecture Notes in Computer Science). doi: 10.1007/978-3-540-30499-9_177

A dual neural network for bi-criteria torque optimization of redundant robot manipulators

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