AUTONOMOUS VISUAL NAVIGATION AND COLLISION-FREE STRATEGY USING DEEP REINFORCEMENT LEARNING
Tracked robots need to achieve safe autonomous steering in various changing environments. In this thesis, a novel end-to-end network architecture is proposed for tracked robots to learn collision-free autonomous navigation through deep reinforcement learning (RL). Specifically, this research improve...
| Main Author: | EJAZ, MUHAMMAD MUDASSIR |
|---|---|
| Format: | Thesis |
| Language: | English |
| Institution: | Universiti Teknologi Petronas |
| Record Id / ISBN-0: | utp-utpedia.20693 / |
| Published: |
2021
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| Subjects: | |
| Online Access: |
http://utpedia.utp.edu.my/20693/1/Muhammad%20Mudassir%20Ejaz_17007900.pdf http://utpedia.utp.edu.my/20693/ |
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