The environment map is the basis of robot navigation. Autonomous robot exploration is the process by which a robot autonomously constructs a map in an unknown environment. How to make the robot reduce the traveling distance when completing an unknown environment is a worthwhile research problem. This work proposes a transformer-based decision network for autonomous exploration and a deep reinforcement learning framework for autonomous robot exploration tasks. Experiments show that our proposed method is feasible and saves an average of 6.7% on distance traveled compared to traditional methods.
A Transformer-Based Robot Autonomous Exploration Method
Lect. Notes Electrical Eng.
International Conference on Autonomous Unmanned Systems ; 2024 ; Shenyang, China September 19, 2024 - September 21, 2024
Proceedings of 4th 2024 International Conference on Autonomous Unmanned Systems (4th ICAUS 2024) ; Kapitel : 24 ; 246-255
28.03.2025
10 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
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