A Gradient Neural Network for online Solving the Time-varying Inverse Kinematics Problem of Four-wheel Mobile Robotic Arm
Date
2021-05-14Author
Zhou, Y
Liu, K
Li, Chunxu
Wang, G
Liu, Y
Sun, Z
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Show full item recordAbstract
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.
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Publisher
IEEE
Journal
2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)
Volume
00
Pagination
391-396
Conference name
2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)
Start date
2021-05-14
Finish date
2021-05-16
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