Toward a Clustering-Based Approach for Self-Adjusting Impact Factors in Robotic Control Model

Toward a Clustering-Based Approach for Self-Adjusting Impact Factors in Robotic Control Model

In mobile robotic control models, control parameters are always generated by sensors' information and a set of Impact Factors (IFs, such as the P-value in the PID model). The IFs take forms of fixed coefficients in control models and need to be pre-defined at design-time. However, when operatin...

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Bibliographic Details
Main Authors: Yuhong Huang, Xinjun Mao, Wanwei Liu, Shuo Yang, Shuo Wang
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Mobile robotic
impact factors
open environment
clustering-based
self-adjusting
Online Access:https://ieeexplore.ieee.org/document/8822939/

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