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2019 | 26 | 1 |

Tytuł artykułu

A multi-layered potential field method for water-jet propelled unmanned surface vehicle local path planning with minimum energy consumption

Autorzy

Warianty tytułu

Języki publikacji

EN

Abstrakty

EN
Focusing on the influence of wind and surface currents on local path planning in the marine environment, a multi-layered potential field (MPF) method is proposed to minimize the energy consumption of a water-jet propelled unmanned surface vehicle (USV). A synthetic environment framework that can incorporate the information of the base potential field layer and the environment layer is constructed first. This framework provides a base for minimizing the energy consumption of the water-jet propelled USV through proper force weighting. For the purpose of USV path planning, the traditional potential field method is extended by including the velocity information of the USV and the approached obstacles to avoid collisions with dynamic obstacles. The proposed method integrates kinematic control to prevent considering the vehicle as a point mass or rigid body. Finally, simulation and comparison experiments are performed to demonstrate the energy-saving efficiency of the proposed local path planning approach for the water-jet propelled USV

Słowa kluczowe

Wydawca

-

Rocznik

Tom

26

Numer

1

Opis fizyczny

p.134-144,fig.,ref.

Twórcy

autor
  • College of Automation, Harbin Engineering University, 145 Nantong Street, Nangang District, 150001 Harbin, China
autor
  • College of Automation, Harbin Engineering University, 145 Nantong Street, Nangang District, 150001 Harbin, China
autor
  • College of Automation, Harbin Engineering University, 145 Nantong Street, Nangang District, 150001 Harbin, China
autor
  • College of Automation, Harbin Engineering University, 145 Nantong Street, Nangang District, 150001 Harbin, China

Bibliografia

  • 1. Liu Z, Zhang Y, Yu X, et al.: Unmanned surface vehicles: An overview of developments and challenges. Annual Reviews in Control, vol.41, pp:71-93, 2016.
  • 2. Lazarowska, Agnieszka.: A new deterministic approach in a decision support system for ship’s trajectory planning. Expert Systems With Applications, vol.71, pp:469-478, 2017.
  • 3. Murphy R, Steimle E, Griffin C, et al. Cooperative use of unmanned sea surface and micro aerial vehicles at Hurricane Wilma. Journal of Field Robotics, 25(3):164–180, 2008. 4. Lazarowska A.: Swarm Intelligence Approach to Safe Ship Control. Polish Maritime Research, 22(4):34-40, 2015.
  • 5. Li W, Ma W.: Simulation on Vessel Intelligent Collision Avoidance Based on Artificial Fish Swarm Algorithm. Polish Maritime Research, 23, 2016.
  • 6. Shen Y, Zhao N, X ia M, et a l.: A Deep Q-Lea rning Net work for Ship Stowage Planning Problem. Polish Maritime Research, 24, 2017.
  • 7. Chen D Z, Szczerba R J, Uhran J.: Planning conditional shortest paths through an unknown environment: a framed-quadtree approach. 1995.
  • 8. Kamon I, Rivlin E.: Sensory based motion planning with global proofs. International Conference on Intelligent Robots and Systems. IEEE Computer Society, 1995.
  • 9. Svec P, Gupta S K.: Automated synthesis of action selection policies for unmanned vehicles operating in adverse environments. Autonomous Robots 149-164, 2012.
  • 10. Goldberg D E.: Genetic Algorithms in Search, Optimization and Machine Learning. xiii(7): 2104–2116,1989.
  • 11. Petres C, Yan P, Patron P, et al.: Path Planning for Autonomous Underwater Vehicles. IEEE Transactions on Robotics, 23(2):331-341, 2007.
  • 12. Lavalle S M.: Rapidly-Exploring Random Trees: A New Tool for Path Planning. Algorithmic & Computational Robotics New Directions, 293-308, 1998.
  • 13. Ge S, Cui Y J.: Dynamic Motion Planning for Mobile Robots Using Potential Field Method. Autonomous Robots, 13(3):207-222, 2002.
  • 14 . Andrews J R, Hogan N.: Impedance Control as a Framework for Implementing Obstacle Avoidance in a Manipulator. Control of Manufacturing Processes and Robotic Systems. 243-251,1983.
  • 15. Zhu Y, Zhang T, Song J.: Study on the Local Minima Problem of Path Planning Using Potential Field Method in Unknown Environments. Acta Automatica Sinica, vol.36(8), pp:1122-1130, 2010.
  • 16. Liu Y, Song R, Bucknall R. A practical path planning and navigation algorithm for an unmanned surface vehicle using the fast marching algorithm. Oceans. IEEE, 2015.
  • 17. Zhu Y, Zhang T, Song J.: Path planning for nonholonomic mobile robots using artificial potential field method. Control Theory & Applications, 27(2):152-158, 2010.
  • 18. Kovács B, Szayer G, Tajti F, et al.: A novel potential field method for path planning of mobile robots by adapting animal motion attributes. Robotics & Autonomous Systems, 82(C):24-34, 2016.
  • 19. Lee T H, Chung H, Myung H.: Multi-resolution path planning for marine surface vehicle considering environmental effects. Oceans. IEEE, 2011.
  • 20. Garau B, Alvarez A, Oliver G.: Path Planning of Autonomous Underwater Vehicles in Current Fields with Complex Spatial Variability: an A* Approach, 2005.
  • 21. Isern-Gonzá lez J, Herná ndez-Sosa D, Ferná ndez-Perdomo E, et al.: Path planning for underwater gliders using iterative optimization. IEEE International Conference on Robotics and Automation, 1538-1543, 2011.
  • 22. Soulignac M.: Feasible and Optimal Path Planning in Strong Current Fields. IEEE Transactions on Robotics, 27(1):89-98, 2011.
  • 23. Lee T, Kim H, Chung H, et al.: Energy efficient path planning for a marine surface vehicle considering heading angle. Ocean Engineering, 107:118-131, 2015.
  • 24. Song R, Liu Y, Bucknall R.: A multi-layered fast marching method for unmanned surface vehicle path planning in a time-variant maritime environment. Ocean Engineering, 129:301-317, 2017.
  • 25. Gong-Xing W U, Jin Z, Lei W, et al.: Design of the basic motion control system for water-jet-propelled unmanned surface vehicle. Control Theory & Applications, 27, 2010.
  • 26. Yue J.: Study on Modeling and Simulation of 6-DOF Motion of Water-jet Propelled Unmanned Surface Vehicle. Dalian Maritime University, 17-60, 2016.

Typ dokumentu

Bibliografia

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