Hybrid-Driven Dynamic Position Prediction of Robot End-Effector Integrating Parametric Dynamic Model and Machine Learning

Hybrid-Driven Dynamic Position Prediction of Robot End-Effector Integrating Parametric Dynamic Model and Machine Learning

Accurate dynamic model and response prediction of industrial robots (IRs) are prerequisites for production optimization before actual operation. In this study, a hybrid-driven dynamic position prediction (HDPP) approach integrating a parametric dynamic model (PDM) and learning-based residual error c...

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Bibliographic Details
Main Authors: Hepeng Ni, Cong Xu, Yingxin Ye, Bo Chen, Shuangsheng Luo, Shuai Ji
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Applied Sciences
Subjects:
robot dynamic position prediction
hybrid-driven model
parametric dynamic model
reinforcement learning-based parameter identification
TCN-LSTM network
Online Access:https://www.mdpi.com/2076-3417/15/2/895
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