IEEE/CAA Journal of Automatica Sinica
Citation: | J. Y. He, J. B. Wen, S. Xiao, and J. C. Yang, “Multi-AUV inspection for process monitoring of underwater oil transportation,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 3, pp. 828–830, Mar. 2023. doi: 10.1109/JAS.2023.123117 |
[1] |
C. Xia, W. Liu, and Q. Deng, “Cost minimization of wireless sensor networks with unlimited-lifetime energy for monitoring oil pipelines,” IEEE/CAA J. Autom. Sinica, vol. 2, no. 3, pp. 290–295, Jul. 2015. doi: 10.1109/JAS.2015.7152663
|
[2] |
X. Yuan, Y. Gu, Y. Wang, C. Yang, and W. Gui, “A deep supervised learning framework for data-driven soft sensor modeling of industrial processes,” IEEE Trans. Neural Networks Learning Systems, vol. 31, no. 11, pp. 4737–4746, Nov. 2020. doi: 10.1109/TNNLS.2019.2957366
|
[3] |
T. Zhou, M. Chen, and J. Zou, “Reinforcement learning based data fusion method for multi-sensors,” IEEE/CAA J. Autom. Sinica, vol. 7, no. 6, pp. 1489–1497, Nov. 2020. doi: 10.1109/JAS.2020.1003180
|
[4] |
K. Zhu and Y. Wang, “Event-triggered sensor fault estimation of unreliable networked unmanned surface vehicle system with correlated noises,” IEEE Trans. Vehicular Technology, vol. 71, no. 3, pp. 2527–2537, Mar. 2022. doi: 10.1109/TVT.2022.3142147
|
[5] |
W. Chen, K. Gu, T. Zhao, G. Jiang, and P. L. Callet, “Semi-reference sonar image quality assessment based on task and visual perception,” IEEE Trans. Multimedia, vol. 23, pp. 1008–1020, Apr. 2020.
|
[6] |
H. Xia, M. A. Khan, Z. Li, and M. Zhou, “Wearable robots for human underwater movement ability enhancement: A survey,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 6, pp. 967–977, Jun. 2022. doi: 10.1109/JAS.2022.105620
|
[7] |
J. Wen, J. Yang, and T. Wang, “Path planning for autonomous underwater vehicles under the influence of ocean currents based on a fusion heuristic algorithm,” IEEE Trans. Vehicular Technology, vol. 70, no. 9, pp. 8529–8544, Sept. 2021. doi: 10.1109/TVT.2021.3097203
|
[8] |
S. Wang, L. Chen, D. Gu, and H. Hu, “Cooperative localization of AUVs using moving horizon estimation,” IEEE/CAA J. Autom. Sinica, vol. 1, no. 1, pp. 68–76, Jan. 2014. doi: 10.1109/JAS.2014.7004622
|
[9] |
Z. Gao and G. Guo, “Fixed-time sliding mode formation control of AUVs based on a disturbance observer,” IEEE/CAA J. Autom. Sinica, vol. 7, no. 2, pp. 539–545, Mar. 2020. doi: 10.1109/JAS.2020.1003057
|
[10] |
H. Li, D. Wang, M. Zhou, Y. Fan, and Y. Xia, “Multi-swarm co-evolution based hybrid intelligent optimization for BI-objective multi-workflow scheduling in the cloud,” IEEE Trans. Parallel Distributed Systems, vol. 33, no. 9, pp. 2183–2197, Sept. 2022. doi: 10.1109/TPDS.2021.3122428
|
[11] |
J. Wang, Q. Zhang, and D. Zhao, “Highway lane change decision-making via attention-based deep reinforcement learning,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 3, pp. 567–569, Mar. 2022. doi: 10.1109/JAS.2021.1004395
|
[12] |
Y. Liu, L. Wan, M. Sheng, T. Liu, and Y. Li, “An improved elbows detection algorithm for underwater blurred images,” in Proc. Conf. Electrical, Automation and Mechanical Engineering, Apr. 2017, pp. 264–267.
|
[13] |
G. P. Drumond, I. P. Pasqualino, B. C. Pinheiro, and S. F. Estefen, “Pipelines, risers and umbilicals failures: A literature review,” Ocean Engineering, vol. 148, pp. 412–425, Jan. 2018. doi: 10.1016/j.oceaneng.2017.11.035
|
[14] |
X. Huang, Y. Li, F. Du, and S. Jin, “Horizontal path following for underactuated AUV based on dynamic circle guidance,” Robotica, vol. 35, no. 4, pp. 876–891, Apr. 2017. doi: 10.1017/S0263574715000867
|
[15] |
Z. Li, J. Deng, R. Lu, Y. Xu, J. Bai, and C. Su, “Trajectory-tracking control of mobile robot systems incorporating neural-dynamic optimized model predictive approach,” IEEE Trans. Systems,Man,Cybernetics: Systems, vol. 46, no. 6, pp. 740–749, Jun. 2016. doi: 10.1109/TSMC.2015.2465352
|
[16] |
R. Yu, Z. Shi, C. Huang, T. Li, and Q. Ma, “Deep reinforcement learning based optimal trajectory tracking control of autonomous underwater vehicle,” in Proc. Chinese Control Conf, Jul. 2017, pp. 495–4965.
|
[17] |
H. Wu, S. Song, K. You, and C. Wu, “Depth control of model-free AUVs via reinforcement learning,” IEEE Trans. Systems,Man,Cybernetics: Systems, vol. 49, no. 12, pp. 2499–2510, Dec. 2019. doi: 10.1109/TSMC.2017.2785794
|
[18] |
Y. Li and X. Chao, “Semi-supervised few-shot learning approach for plant diseases recognition,” Plant Methods, vol. 17, no. 68, pp. 1–10, Jun. 2021.
|
[19] |
M. Xi, J. Yang, J. Wen, H. Liu, Y. Li, and H. H. Song, “Comprehensive ocean information-enabled AUV path planning via reinforcement learning,” IEEE Internet of Things J., vol. 9, no. 18, pp. 17440–17451, Sept. 2022.
|
[20] |
J. Yang, S. Xiao, A. Li, W. Lu, X. Gao, and Y. Li, “MSTA-Net: Forgery detection by generating manipulation trace based on multi-scale self-texture attention,” IEEE Trans. Circuits Systems Video Technology, vol. 32, no. 7, pp. 4854–4866, Jul. 2022. doi: 10.1109/TCSVT.2021.3133859
|