Jiawen Li, Xiang Cao, and Xueyou Huang


  1. [1] S. Cui, Y. Wang, and S. Wang, Real-time perception andpositioning for creature picking of an underwater vehicle, IEEETransactions on Vehicular Technology, 69(4), 2020, 3783–3792.
  2. [2] Z. Guan, C. Hou, S. Zhou, and Z. Guo, Research on underwatertarget recognition technology based on neural network, WirelessCommunications and Mobile Computing, 2022, 2022, 4197178.
  3. [3] N. Kapetanovi´c and K. Krˇcmar, Tether management system forautonomous inspection missions in mariculture using an ASVand an ROV, IFAC-PapersOnLine, 55(31), 2022, 327–332.
  4. [4] Y. Zhao, Y. Shi, and Z. Wang, The improved YOLOv5 algorithmand its application in small target detection, Proc. InternationalConf. on Intelligent Robotics and Applications, Cham, 2022,679–688.
  5. [5] J. Yun, D. Jiang, Y. Liu, and Y. Sun, Real-time targetdetection method based on lightweight convolutional neuralnetwork, Frontiers in Bioengineering and Biotechnology, 10,2022, 861286.
  6. [6] K. Hu, J. Jin, and F. Zheng, Overview of behavior recognitionbased on deep learning, Artificial Intelligence Review, 56, 2023,1–33.
  7. [7] R. Girshick, J. Donahue, T. Darrell, and J. Malik, Richfeature hierarchies for accurate object detection and semanticsegmentation, Proc. 2014 IEEE Conf. on Computer Vision andPattern Recognition, Columbus, OH, 2014, 580–587.
  8. [8] J. Redmon, S. Divvala, and R. Girshick, You only look once:Unified, real-time object detection, Proc. IEEE Conf. onComputer Vision and Pattern Recognition, Las Vegas, NV,2016, 779–788.
  9. [9] S. Ren, K. He, R. Girshick, and J. Sun, Faster R-CNN: Towardsreal-time object detection with region proposal networks,237Advances in Neural Information Processing Systems, 9199,2015, 2969239–2969250.
  10. [10] J. Redmon and A Farhadi, YOLO9000: Better, faster, stronger,Proc. IEEE Conf. Computer Vision and Pattern Recognition,Honolulu, HI, 2017, 7263–7271.
  11. [11] W. Liu, D. Anguelov, and D. Erhan, SSD: Single shot multiboxdetector, Proc. European Conf. on Computer Vision, Cham,2016, 21–37.
  12. [12] X. Wang, X. Hua, and F. Xiao, Multi-object detection in trafficscenes based on improved SSD, Electronics, 7(11), 2018, 302.
  13. [13] F. Han, J. Yao, and H. Zhu, Underwater image processingand object detection based on deep CNN method, Journal ofSensors, 2020, 2020, 6707328.
  14. [14] D. Jiang, G. Li, and Y. Sun, Manipulator grabbing positiondetection with information fusion of color image and depthimage using deep learning, Journal of Ambient Intelligence andHumanized Computing, 12(12), 2021, 10809–10822.
  15. [15] H. Sun, X. Cui, and Z. Song, Precise grabbing of overlappingobjects system based on end-to-end deep neural network,Computer Communications, 176, 2021, 138–145.
  16. [16] F. Mei and X. Gao, Target recognition and grabbing positioningmethod based on convolutional neural network, MathematicalProblems in Engineering, 2022, 2022, 4360346.
  17. [17] G.U. Shaokui, and L.I. Longyan , Research status of robotgrab detection based on vision, Asian Journal of Research inComputer Science, 14(4), 2022, 21–35.
  18. [18] L. Trottier, P. Giguere, and B. Chaib-Draa, Convolutionalresidual network for grasp localization, Proc. 2017 14th Conf.on Computer and Robot Vision (CRV), Edmonton, AB, 2017,168–175.
  19. [19] T.H. Nguyen, T.T. Nguyen, and T.V. Tran, A method forlocalizing and grasping objects in a picking robot system usingkinect camera, Proc. International Conf. on Intelligent HumanComputer Interaction, Cham, 2021, 21–26.
  20. [20] M.W. Walker, Manipulator kinematics and the epsilon algebra,IEEE Journal on Robotics and Automation, 4(2), 1988, 186–192.
  21. [21] D. Quillen, E. Jang, O. Nachum, C. Finn, J. Ibarz, and S. Levine,Deep reinforcement learning for vision-based robotic grasping:A simulated comparative evaluation of off-policy methods, Proc.2018 IEEE International Conf.on Robotics and Automation(ICRA), Brisbane, QLD, 2018, 6284–6291.
  22. [22] A. Jebelli, H. Chaoui, A. Mahabadi, and B. Dhillon, Trackingand mapping system for an underwater vehicle in real positionusing sonar system, International Journal of Robotics andAutomation, 37, 2022, 124–134.
  23. [23] Z. Geng, Study on the position control of electric cylinder basedon fuzzy adaptive PID, International Journal of Robotics andAutomation, 35(3), 2020, 242–247.
  24. [24] C. Li, H. Gao, and Y. Yang, Segmentation method of high-resolution remote sensing image for fast target recognition,International Journal of Robotics and Automation, 34(3), 2019,4597–4618.

Important Links:

Go Back