Advances in International Computer Science

The research on optimizing autonomous navigation algorithms for unmanned systems based on deep learning aims to improve the navigation accuracy and robustness of unmanned systems in complex environments. Traditional navigation algorithms often perform poorly in dynamic and uncertain environments, failing to effectively handle real-time environmental changes. This paper proposes a new deep learning method that optimizes the path planning and positioning strategies of unmanned systems by training neural network models, thereby enhancing navigation efficiency. Experimental verification shows that the proposed algorithm has higher accuracy and adaptability than traditional algorithms in practical applications. This research provides new ideas and optimization schemes for the development of autonomous navigation technology for unmanned systems, and has important theoretical and application value.

Deep learning; Unmanned systems; Autonomous navigation; Algorithm optimization; Path planning