UGV Navigation Optimization Aided by Reinforcement Learning-Based Path Tracking
The success of robotic, such as UGV systems, largely benefits from the fundamental capability of autonomously finding collision-free path(s) to commit mobile tasks in routinely rough and complicated environments. Optimization of navigation under such circumstance has long been an open problem: 1) to...
Main Authors: | , , , |
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Format: | Article |
Language: | English |
Published: |
IEEE
2018-01-01
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Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/8476521/ |