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Design and Experimental Validation of Deep Reinforcement Learning-Based Fast Trajectory Planning and Control for Mobile Robot in Unknown Environment

Chai, Runqi; Niu, Hanlin; Carrasco, Joaquin; Arvin, Farshad; Yin, Hujun; Lennox, Barry

Authors

Runqi Chai

Hanlin Niu

Joaquin Carrasco

Hujun Yin

Barry Lennox



Citation

Chai, R., Niu, H., Carrasco, J., Arvin, F., Yin, H., & Lennox, B. (2024). Design and Experimental Validation of Deep Reinforcement Learning-Based Fast Trajectory Planning and Control for Mobile Robot in Unknown Environment. IEEE Transactions on Neural Networks and Learning Systems, 35(4), 5778-5792. https://doi.org/10.1109/tnnls.2022.3209154

Journal Article Type Article
Acceptance Date Sep 18, 2022
Online Publication Date Oct 10, 2022
Publication Date 2024-04
Deposit Date Oct 12, 2022
Journal IEEE Transactions on Neural Networks and Learning Systems
Print ISSN 2162-237X
Electronic ISSN 2162-2388
Publisher Institute of Electrical and Electronics Engineers
Peer Reviewed Peer Reviewed
Volume 35
Issue 4
Pages 5778-5792
DOI https://doi.org/10.1109/tnnls.2022.3209154
Public URL https://durham-repository.worktribe.com/output/1189344
Related Public URLs https://research.manchester.ac.uk/en/publications/design-and-experimental-validation-of-deep-reinforcement-learning



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