Human-in-the-Loop Reinforcement Learning to Track Excavation Paths for a Hydraulic Excavator in a Short Period of Time

Human-in-the-Loop Reinforcement Learning to Track Excavation Paths for a Hydraulic Excavator in a Short Period of Time

The construction industry faces a severe shortage of skilled operators. One promising approach to mitigate this problem is to automate construction machinery, particularly hydraulic excavators, which have a wide range of applications. However, it is challenging to automate hydraulic excavators due t...

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Bibliographic Details
Main Authors: Tatsuya Mori, Tatsuya Yoshimoto, Hiroshi Yoshida
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Deep reinforcement learning
human-in-the-loop learning
hydraulic excavators
path tracking
world model
Online Access:https://ieeexplore.ieee.org/document/11062842/
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