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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. (2022). 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, https://doi.org/10.1109/tnnls.2022.3209154

Journal Article Type Article
Acceptance Date Sep 20, 2022
Online Publication Date Oct 10, 2022
Publication Date Oct 10, 2022
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
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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