Dynamic Path Planning Of Unmanned Surface Vehicle Based On Genetic Algorithm With Sliding Curve Guidance System

Rusdhianto Effendie Abdul Kadir, Mochammad Sahal, Nurlita Gamayanti, Fian Ilham Pratama


Unmanned Surface Vehicle (USV) is an unmanned ship that is controlled through a remote control system (manual) or automatic control system (autopilot), move due to the thrust force from thruster machine and can turning due to the deflection angle of rudder. The USV path planning system becomes an important task so that the ship can make the global trajectory with the minimum travel distance according to the desired navigation while at the same able to avoid various obstacles from local dangerous situations that have the potential for collisions. To be able to do dynamic USV path planning, the Genetic Algorithm method with a sliding curve guidance system and PID MRAC controller is used. The use of this method gives smooth ship track performance with shortest distance in a 400x400 square meter map with static and dynamic obstacles. In a dynamic environment, the path replanning process that takes place in 0,98 seconds is able to find a new path that does not collide the obstacles. For the purposes of algorithm validation, the simulation is performed using MATLAB software with real ship parameters of 6 meters length USV.

Keywords: dynamic and static obstacle, genetic algorithm, guidance system, path planning, PID MRAC, sliding curve, USV. 

Full Text:



JC. Mohanta; DR. Parhi; SK. Patel, “Path planning strategy for

autonomous mobile robot navigation using Petri-GA optimization.

Computers and Electrical Engineering”, 2011.

J. C. Latombe, "Robot motion planning," Kulwer Academic

publishers, Boston, MA, 1991.

T. Lozano-Perez and M. Wesley, "An algorithm for planning

collision-Free paths among polyhedral obstacles", 1979.

D. E. Goldberg, "Genetic algorithms in search, optimization and

machine learning", Addison- Wesley publishing company, 1989.

Stateczny, A.; Burdziakowski, P. Universal autonomous control and

management system for multipurpose unmanned surface vessel.

Polish Marit. Res. 2019

Stateczny, A.; Kazimierski, W.; Gronska-Sledz, D.; Motyl, W. The

Empirical Application of Automotive 3D Radar Sensor for Target

Detection for an Autonomous Surface Vehicle’s Navigation. Remote

Sens. 2019.

K. D. Do; J. Pan, “Control of Ships and Underwater Vehicles,”

Springer- Verlag, 2009.

Y. Lu; Z. Xue; G. Xia; L. Zhang, “A Survey on Vision-based UAV

Navigation”, 2018.

Tutorials Point n.d., the Companies Act, accessed 10 June 2020,


Sujit, P. B., Srikanth Saripalli, and Joao Borges Sousa. "Unmanned

aerial vehicle path following: A survey and analysis of algorithms for

fixed-wing unmanned aerial vehicless." IEEE Control Systems

Magazine 34.1 (2014): 42-59.

N. Gamayanti, “Maneuver And Waypoints Control of Unmanned

Surface Vehicles Using Model Reference Adaptive Control (MRAC)

Based Pid Controller”, 2019

DOI: https://doi.org/10.12962/jaree.v5i1.165


  • There are currently no refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.