A Gradient Neural Network for online Solving the Time-varying Inverse Kinematics Problem of Four-wheel Mobile Robotic Arm

Yanpeng Zhou; K Liu; Chunxu Li; Gang Wang; Y Liu; Zhongbo Sun

doi:10.1109/ddcls52934.2021.9455633

A Gradient Neural Network for online Solving the Time-varying Inverse Kinematics Problem of Four-wheel Mobile Robotic Arm

Yanpeng Zhou, K Liu, Chunxu Li, Gang Wang, Y Liu, Zhongbo Sun

School of Engineering, Computing and Mathematics

Changchun University of Technology

Research output: Contribution to journal › Conference proceedings published in a journal › peer-review

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Abstract

In this paper, a gradient neural network (GNN) is presented, analyzed and discussed to solve the time-varying inverse kinematics solution of the four-wheel mobile robotic arm, which can approximate the time varying inverse kinematics solution. A monolithic kinematics model of mobile robotic arm is established, and the inverse kinematics solution can synchronously coordinate the control of the mobile platform and the robotic arm to accomplish the task of the end-executor. Besides, the computer numerical results are provided to attest validity and high exactitude of GNN model in settling the time-varying inverse kinematics of a four-wheel mobile robotic arm.

Original language	English
Pages (from-to)	391-396
Number of pages	0
Journal	2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)
Volume	0
Issue number	0
DOIs	https://doi.org/10.1109/ddcls52934.2021.9455633
Publication status	Published - 14 May 2021
Event	2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS) - Duration: 14 May 2021 → 16 May 2021

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title = "A Gradient Neural Network for online Solving the Time-varying Inverse Kinematics Problem of Four-wheel Mobile Robotic Arm",

abstract = "In this paper, a gradient neural network (GNN) is presented, analyzed and discussed to solve the time-varying inverse kinematics solution of the four-wheel mobile robotic arm, which can approximate the time varying inverse kinematics solution. A monolithic kinematics model of mobile robotic arm is established, and the inverse kinematics solution can synchronously coordinate the control of the mobile platform and the robotic arm to accomplish the task of the end-executor. Besides, the computer numerical results are provided to attest validity and high exactitude of GNN model in settling the time-varying inverse kinematics of a four-wheel mobile robotic arm.",

author = "Yanpeng Zhou and K Liu and Chunxu Li and Gang Wang and Y Liu and Zhongbo Sun",

year = "2021",

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A Gradient Neural Network for online Solving the Time-varying Inverse Kinematics Problem of Four-wheel Mobile Robotic Arm. / Zhou, Yanpeng; Liu, K; Li, Chunxu et al.
In: 2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS), Vol. 0, No. 0, 14.05.2021, p. 391-396.

Research output: Contribution to journal › Conference proceedings published in a journal › peer-review

TY - JOUR

T1 - A Gradient Neural Network for online Solving the Time-varying Inverse Kinematics Problem of Four-wheel Mobile Robotic Arm

AU - Zhou, Yanpeng

AU - Liu, K

AU - Li, Chunxu

AU - Wang, Gang

AU - Liu, Y

AU - Sun, Zhongbo

PY - 2021/5/14

Y1 - 2021/5/14

N2 - In this paper, a gradient neural network (GNN) is presented, analyzed and discussed to solve the time-varying inverse kinematics solution of the four-wheel mobile robotic arm, which can approximate the time varying inverse kinematics solution. A monolithic kinematics model of mobile robotic arm is established, and the inverse kinematics solution can synchronously coordinate the control of the mobile platform and the robotic arm to accomplish the task of the end-executor. Besides, the computer numerical results are provided to attest validity and high exactitude of GNN model in settling the time-varying inverse kinematics of a four-wheel mobile robotic arm.

AB - In this paper, a gradient neural network (GNN) is presented, analyzed and discussed to solve the time-varying inverse kinematics solution of the four-wheel mobile robotic arm, which can approximate the time varying inverse kinematics solution. A monolithic kinematics model of mobile robotic arm is established, and the inverse kinematics solution can synchronously coordinate the control of the mobile platform and the robotic arm to accomplish the task of the end-executor. Besides, the computer numerical results are provided to attest validity and high exactitude of GNN model in settling the time-varying inverse kinematics of a four-wheel mobile robotic arm.

U2 - 10.1109/ddcls52934.2021.9455633

DO - 10.1109/ddcls52934.2021.9455633

M3 - Conference proceedings published in a journal

SN - 2767-9861

VL - 0

SP - 391

EP - 396

JO - 2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)

JF - 2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)

IS - 0

T2 - 2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)

Y2 - 14 May 2021 through 16 May 2021

ER -

A Gradient Neural Network for online Solving the Time-varying Inverse Kinematics Problem of Four-wheel Mobile Robotic Arm

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