Prakash, Surya and Sharma, Bibhya N. (2025) Navigating Dynamic Environments with LSTM, Dijkstra, and Lyapunov: A Unified Approach for Autonomous Pathfinding and Control. In: Business Intelligence and Data Analytics. Smart Innovation, Systems and Technologies . Springer Nature, Singapore, pp. 477-491. ISBN 978-981-97-7716-7
Full text not available from this repository.Abstract
This study introduces an approach to navigate dynamic environments through the fusion of Long Short-Term Memory (LSTM) networks, Dijkstra’s algorithm, and Lyapunov stability theory. This integrated method capitalizes on the strengths of each component: LSTM’s capability for predicting dynamic obstacles, Dijkstra’s algorithm for efficient pathfinding, and Lyapunov’s theory for ensuring navigational stability. By synergizing these elements, the approach provides a robust solution for autonomous systems to navigate unpredictable terrains with enhanced safety, reliability, and efficiency. Through theoretical analysis and empirical evaluation, this research demonstrates the effectiveness of the integrated framework in improving the autonomy, reliability, and safety of navigation systems. The findings highlight the potential of combining machine learning, algorithmic pathfinding, and control theory to enhance the navigational strategies of autonomous vehicles and robots, particularly in unpredictable environments.
| Item Type: | Book Chapter |
|---|---|
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > T Technology (General) |
| Divisions: | School of Information Technology, Engineering, Mathematics and Physics (STEMP) |
| Depositing User: | Ms Shalni Sanjana |
| Date Deposited: | 06 Apr 2025 22:38 |
| Last Modified: | 06 Apr 2025 22:38 |
| URI: | https://repository.usp.ac.fj/id/eprint/14916 |
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