Pinchu2002 / Adaptive-Robot-Path-Planning-in-Dynamic-and-Uncertain-Environement-Using-Reinforcement-LearningView on GitHub
Adaptive Robot Path Planning in Dynamic Environments: Developed a Deep Q-Learning (DQN) model with Transformer architecture and positional encoding for efficient robot navigation in dynamic environments. Integrated Prioritized Replay Buffer for optimized training and implemented a Pygame-based simulation to test adaptability.
☆24Dec 9, 2024Updated last year
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