ETQ-learning: an improved Q-learning algorithm for path planning
Author:
Funder
Special Project for Research and Development in Key areas of Guangdong Province
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11370-024-00544-3.pdf
Reference28 articles.
1. Costa MM, Silva MF (2019) A survey on path planning algorithms for mobile robots. In: 2019 IEEE international conference on autonomous robot systems and competitions (ICARSC), IEEE, pp. 1–7
2. Wang H, Lou S, Jing J, Wang Y, Liu W, Liu T (2022) The EBS-A* algorithm: an improved A* algorithm for path planning. PLoS ONE 17(2):e0263841
3. Wang H, Qi X, Lou S, Jing J, He H, Liu W (2021) An efficient and robust improved A* algorithm for path planning. Symmetry 13(11):2213
4. Li D, Yin W, Wong WE, Jian M, Chau M (2021) Quality-oriented hybrid path planning based on A* and Q-learning for unmanned aerial vehicle. IEEE Access 10:7664–7674
5. Wang B, Liu Z, Li Q, Prorok A (2020) Mobile robot path planning in dynamic environments through globally guided reinforcement learning. IEEE Robot Autom Lett 5(4):6932–6939
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