Design and implementation of global path planning system for unmanned surface vehicle among multiple task points

Purpose – This paper aims to propose a new method for combining global path planning with local path planning, to provide an efficient solution for unmanned surface vehicle (USV) path planning despite the changeable environment. Path planning is the key issue of USV navigation. A lot of research works were done on the global and local path planning. However, little attention was given to combining global path planning with local path planning. Design/methodology/approach – A search of shortcut Dijkstra algorithm was used to control the USV in the global path planning. When the USV encounters unknown obstacles, it switches to our modified artificial potential field (APF) algorithm for local path planning. The combinatorial method improves the approach of USV path planning in complex environment. Findings – The method in this paper offers a solution to the issue of path planning in changeable or unchangeable environment, and was confirmed by simulations and experiments. The USV follows the global path based on the search of shortcut Dijkstra algorithm. Both USV achieves obstacle avoidances in the local region based on the modified APF algorithm after obstacle detection. Both the simulation and experimental results demonstrate that the combinatorial path planning method is more efficient in the complex environment. Originality/value – This paper proposes a new path planning method for USV in changeable environment. The proposed method is capable of efficient navigation in changeable and unchangeable environment.

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Study on intelligent collision avoidance and recovery path planning system for the waterjet-propelled unmanned surface vehicle

Ocean Engineering ◽

10.1016/j.oceaneng.2019.04.076 ◽

2019 ◽

Vol 182 ◽

pp. 489-498 ◽

Cited By ~ 6

Author(s):

Binghua Shi ◽

Yixin Su ◽

Chen Wang ◽

Lili Wan ◽

Yi Luo

Keyword(s):

Path Planning ◽

Collision Avoidance ◽

Planning System ◽

Unmanned Surface Vehicle

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

JAREE (Journal on Advanced Research in Electrical Engineering) ◽

10.12962/jaree.v5i1.165 ◽

2021 ◽

Vol 5 (1) ◽

Author(s):

Rusdhianto Effendie Abdul Kadir ◽

Mochammad Sahal ◽

Nurlita Gamayanti ◽

Fian Ilham Pratama

Keyword(s):

Genetic Algorithm ◽

Control System ◽

Path Planning ◽

Dynamic Environment ◽

Guidance System ◽

Planning System ◽

Unmanned Surface Vehicle ◽

Dynamic Path Planning ◽

Genetic Algorithm Method ◽

Unmanned Ship

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.

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