### Abstract

This paper proposes a method to calculate manipulator inverse dynamics using a neural network. In this method, two sets of neural networks are prepared. One is for the elements of inertia moment matrix, and the other is for gravitational force. Each input for the network is only a joint position. Teacher signals of each network are also calculated using only a joint position, and therefore learning of each network is fast. The neural network, which acquires a model of inertia moment matrix, is used to calculate inertial force, centrifugal force and Coriolis force. In particular, the terms of centrifugal force and Coriolis force are calculated using a characteristic of manipulator dynamics and structure of the neural network. This method can be applied to the wide area data of joint positions, joint velocities and joint accelerations to calculate manipulator inverse dynamics. To show the validity of this method, the inverse dynamics of a two-dimensional manipulator are calculated.

Original language | English |
---|---|

Pages (from-to) | 839-844 |

Number of pages | 6 |

Journal | transactions of the japan society of mechanical engineers series c |

Volume | 59 |

Issue number | 559 |

DOIs | |

Publication status | Published - Jan 1 1993 |

### Fingerprint

### All Science Journal Classification (ASJC) codes

- Mechanics of Materials
- Mechanical Engineering
- Industrial and Manufacturing Engineering

### Cite this

**A Neural Network System for Calculation of Inverse Dynamics for Manipulators.** / Yamamoto, Motoji; Suematsu, Hisashi.

Research output: Contribution to journal › Article

*transactions of the japan society of mechanical engineers series c*, vol. 59, no. 559, pp. 839-844. https://doi.org/10.1299/kikaic.59.839

}

TY - JOUR

T1 - A Neural Network System for Calculation of Inverse Dynamics for Manipulators

AU - Yamamoto, Motoji

AU - Suematsu, Hisashi

PY - 1993/1/1

Y1 - 1993/1/1

N2 - This paper proposes a method to calculate manipulator inverse dynamics using a neural network. In this method, two sets of neural networks are prepared. One is for the elements of inertia moment matrix, and the other is for gravitational force. Each input for the network is only a joint position. Teacher signals of each network are also calculated using only a joint position, and therefore learning of each network is fast. The neural network, which acquires a model of inertia moment matrix, is used to calculate inertial force, centrifugal force and Coriolis force. In particular, the terms of centrifugal force and Coriolis force are calculated using a characteristic of manipulator dynamics and structure of the neural network. This method can be applied to the wide area data of joint positions, joint velocities and joint accelerations to calculate manipulator inverse dynamics. To show the validity of this method, the inverse dynamics of a two-dimensional manipulator are calculated.

AB - This paper proposes a method to calculate manipulator inverse dynamics using a neural network. In this method, two sets of neural networks are prepared. One is for the elements of inertia moment matrix, and the other is for gravitational force. Each input for the network is only a joint position. Teacher signals of each network are also calculated using only a joint position, and therefore learning of each network is fast. The neural network, which acquires a model of inertia moment matrix, is used to calculate inertial force, centrifugal force and Coriolis force. In particular, the terms of centrifugal force and Coriolis force are calculated using a characteristic of manipulator dynamics and structure of the neural network. This method can be applied to the wide area data of joint positions, joint velocities and joint accelerations to calculate manipulator inverse dynamics. To show the validity of this method, the inverse dynamics of a two-dimensional manipulator are calculated.

UR - http://www.scopus.com/inward/record.url?scp=0027560124&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0027560124&partnerID=8YFLogxK

U2 - 10.1299/kikaic.59.839

DO - 10.1299/kikaic.59.839

M3 - Article

AN - SCOPUS:0027560124

VL - 59

SP - 839

EP - 844

JO - Nippon Kikai Gakkai Ronbunshu, C Hen/Transactions of the Japan Society of Mechanical Engineers, Part C

JF - Nippon Kikai Gakkai Ronbunshu, C Hen/Transactions of the Japan Society of Mechanical Engineers, Part C

SN - 0387-5024

IS - 559

ER -