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Error Mitigation Algorithm Based on Bidirectional Fitting Method for Collision Avoidance of Unmanned Surface Vehicle Cover

Error Mitigation Algorithm Based on Bidirectional Fitting Method for Collision Avoidance of Unmanned Surface Vehicle

Open Access
|Jan 2019

References

  1. 1. Li W. F., Ma W. Y., Simulation on Vessel Intelligent Collision
  2. Avoidance Based on Artificial Fish Swarm Algorithm. Polish
  3. Maritime Research, 2016, 23:138-143.10.1515/pomr-2016-0058
  4. 2. Campbell S., Naeem W., Irwin G.W., A review on improving
  5. the autonomy of unmanned surface vehicles through intelligent
  6. collision avoidance maneuver. Annual Reviews in Control, 2012, 36(2):267-283.10.1016/j.arcontrol.2012.09.008
  7. 3. Larson J., Bruch M., Halterman R., Rogers J., Webster R., Advances in Autonomous Obstacle Avoidance for Unmanned
  8. Surface Vehicles. Space and Naval Warfare Systems Center, San Diego, CA, 2007.
  9. 4. U.S. department Homeland Security/U.S. Coast Guard, “Navigation Rules,” Paradise Cay Publications, 2010.
  10. 5. Kim, H., Park, B., Myung, H., Curvature path planning
  11. with high resolution graph for unmanned surface vehicle.
  12. Robot Intelligence Technology and Applications, 2013, 208:147-154.
  13. 6. Riccardo P., Sanjay S., Jian W., Andrew M., Robert S., Obstacle Avoidance Approaches for Autonomous Navigation
  14. of Unmanned Surface Vehicles. Journal of Navigation, 2017, 71(1): 1-16.
  15. 7. Kuwata Y., Wolf M. T., Zarzhitsky D., Huntsberger T. L., Safe maritime autonomous navigation with COLREGS, using
  16. velocity obstacles, IEEE Journal of Oceanic Engineering, 2014, 39(1):110-119.10.1109/JOE.2013.2254214
  17. 8. Zhao Y. X., Wang L., Peng Sh., A real-time collision avoidance
  18. learning system for Unmanned Surface Vessels. Neurocomputing, 2016, 182:255-266.10.1016/j.neucom.2015.12.028
  19. 9. Park J. H., Kim J. W., Son N. S., Passive target tracking of marine
  20. traffic ships using onboard monocular camera for unmanned
  21. surface vessel. Ectronics letters, 2015, 51(31):987-989.10.1049/el.2015.1163
  22. 10. Wang H., Mou, X. Zh., Mou W., Vision based Long Range
  23. Object Detection and Tracking for Unmanned Surface Vehicle.
  24. Proceedings of the 2015 7th IEEE International Conference
  25. on Cybernetics and Intelligent Systems and Robotics, Automation and Mechatronics, Cambodia, 2015:101-105.
  26. 11. Lazarowska A., Swarm Intelligence Approach to Safe Ship
  27. Control. Polish Maritime Research, 2015, 22(4): 34-40.10.1515/pomr-2015-0068
  28. 12. Zhong K., Lei X., Li SQ., Wiener filter preprocessing for
  29. OFDM systems in the presence of both nonstationary and
  30. stationary phase noises. EURASIP Journal on Advances in
  31. Signal Processing, 2013(7):1-9.
  32. 13. Widrow B., Hoff M., Adaptive switch circuits. IRE Wescom, Convertion Record, Part 4, 1966:96-104.
  33. 14. Wang X., Liu J. H., Zhou Q. F., Real-Time Multi-Target
  34. Localization from Unmanned Aerial Vehicles. Sensors, 2016, 17(1):33-43.10.3390/s17010033529860628029145
  35. 15. Dichev D., Koev H., Bakalova T., An Algorithm for Improving
  36. the Accuracy of Systems Measuring Parameters if Moving
  37. Objects, Metrology and Measurement Systems, 2016, 23(4):555-565.10.1515/mms-2016-0041
  38. 16. Borodachev S. M., Recursive Least Squares Method of
  39. Regression Coefficients Estimation as a Special Case of Kalman
  40. Filter. International Conference on Numerical Analysis and
  41. Applied Mathematics, Rhodes, 2015:23-29.
  42. 17. Singer R. A., Estimating Optimal Tracking Filter Performance
  43. for Manned Maneuvering Targets, IEEE Transaction on
  44. Aerospace and Electronic Systems, l970, 6(4):473-483.
  45. 18. Zhou Zh., Liu J. M., Tan X. J., MCS Model Based on Jerk
  46. Input Estimation and Nonlinear Tracking Algorithm. Journal
  47. of Beijing University of Aeronautics and Astronautics, 2013, 39(10): 1397-1402.
  48. 19. Zhu W., Wang W., Yuan G., An Improved Interacting Multiple
  49. Model Filtering Algorithm Based on the Cubature Kalman
  50. Filter for Maneuvering Target Tracking. Sensors, 2016, 16(6): 805-815.10.3390/s16060805493423127258285
  51. 20. Afshari H. H., Al-Ani D., Habibi S., A New Adaptive Control
  52. Scheme Based on the Interacting Multiple Model (IMM)
  53. Estimation. Journal of Mechanical Science & Technology, 2016, 30 (6):2759-2767.10.1007/s12206-016-0237-z
  54. 21. Jin B., Jiu B., Su T., Switched Kalman Filter-Interacting
  55. Multiple Model Algorithm Based on Optimal Autoregressive
  56. Model for Manoeuvring Target Tracking. IET Radar Sonar
  57. and Navigation, 2015, 9(2): 199-209.10.1049/iet-rsn.2014.0142
  58. 22. Yousef, M. T., Ali, H. E. I., Habashy, S. M., Adaptive Controller
  59. based PSO with Virtual Sensor for Obstacle Avoidance in
  60. Dynamic Environments, Radio Science Conference, 2014, 228-235.
  61. 23. Liu Y. Ch., Bucknall R., Path Planning Algorithm for
  62. Unmanned Surface Vehicle Formations in a Practical Maritime
  63. Environment, Ocean Engineering, 2015, 97:126-144.10.1016/j.oceaneng.2015.01.008
DOI: https://doi.org/10.2478/pomr-2018-0127 | Journal eISSN: 2083-7429 | Journal ISSN: 1233-2585
Language: English
Page range: 13 - 20
Published on: Jan 18, 2019
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2019 Lifei Song, Zhuo Chen, Yunsheng Mao, Zaopeng Dong, Zuquan Xiang, published by Gdansk University of Technology
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.