Reinforcement based mobile robot path planning with improved dynamic window approach in unknown environment
Author:
Funder
Natural Science Foundation of Jiangsu Province
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence
Link
https://link.springer.com/content/pdf/10.1007/s10514-020-09947-4.pdf
Reference58 articles.
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2. Azzabi, A., & Nouri, K. (2019). An advanced potential field method proposed for mobile robot path planning. Transactions of the Institute of Measurement and Control,. https://doi.org/10.1177/0142331218824393.
3. Ballesteros, J., Urdiales, C., Velasco, A. B. M., & Ramos-Jimenez, G. (2017). A biomimetical dynamic window approach to navigation for collaborative control. IEEE Transactions on Human–Machine Systems, 47(6), 1123–1133.
4. Bayili, S., & Polat, F. (2011). Limited-damage A*: A path search algorithm that considers damage as a feasibility criterion. Knowledge-Based Systems, 24(4), 501–512.
5. Best, G., Faigl, J., & Fitch, R. (2017). Online planning for multi-robot active perception with self-organising maps. Autonomous Robots, 42(4), 715–738.
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