Improved Position Estimation Algorithm of Agricultural Mobile Robots Based on Multisensor Fusion and Autoencoder Neural Network

Improved Position Estimation Algorithm of Agricultural Mobile Robots Based on Multisensor Fusion and Autoencoder Neural Network

High-precision position estimations of agricultural mobile robots (AMRs) are crucial for implementing control instructions. Although the global navigation satellite system (GNSS) and real-time kinematic GNSS (RTK-GNSS) provide high-precision positioning, the AMR accuracy decreases when the signals i...

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Bibliographic Details
Main Authors: Peng Gao, Hyeonseung Lee, Chan-Woo Jeon, Changho Yun, Hak-Jin Kim, Weixing Wang, Gaotian Liang, Yufeng Chen, Zhao Zhang, Xiongzhe Han
Format: Article
Language:English
Published: MDPI AG 2022-02-01
Series:Sensors
Subjects:
Kalman filter (KF)
inertial measurement unit (IMU)
global navigation satellite system (GNSS)
autoencoder neural network
agricultural mobile robots (AMRs)
Online Access:https://www.mdpi.com/1424-8220/22/4/1522

Internet

https://www.mdpi.com/1424-8220/22/4/1522

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