2018Unpublished venueRequires access

A Research on Intelligent Obstacle Avoidance for Unmanned Surface Vehicles

Tong Xinchi, Huajun Zhang, Wenwen Chen, Zhao Peimin, Zhiwen Leng, Kai Cheng

Open publisher page 20 citations

Abstract

In order to solve the problem of intelligent obstacle avoidance when an unmanned surface vehicle navigates autonomously in a complex marine environment, the obstacle avoidance is divided into stationary obstacle avoidance and dynamic obstacle avoidance. Based on the ant colony algorithm, the local path planning of the simplified model of the unmanned surface vehicles is carried out to achieve the static collision avoidance. And in accordance with the Convention on the International Regulations for Preventing Collisions at Sea (COLREGS), a dynamic obstacle model is established and calculated to obtain the changes of the speed and course of the unmanned surface vehicles under different encounters. It is shown through the simulations that the proposed approach considering multiple factors can achieve the automatic collision avoidance.

About this research paper

What this paper is about

In order to solve the problem of intelligent obstacle avoidance when an unmanned surface vehicle navigates autonomously in a complex marine environment, the obstacle avoidance is divided into stationary obstacle avoidance and dynamic obstacle avoidance. Based on the ant colony algorithm, the local path planning of the simplified model of the unmanned surface vehicles is carried out to achieve the static collision avoidance. And in accordance with the Convention on the International Regulations for Preventing Collisions at Sea (COLREGS), a dynamic obstacle model is established and calculated to obtain the changes of the speed and course of the unmanned surface vehicles under different encounters. It is shown through the simulations that the proposed approach considering multiple factors can achieve the automatic collision avoidance.

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OpenAlex reports 20 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

In order to solve the problem of intelligent obstacle avoidance when an unmanned surface vehicle navigates autonomously in a complex marine environment, the obstacle avoidance is divided into stationary obstacle avoidance and dynamic obstacle avoidance. Based on the ant colony algorithm, the local path planning of the simplified model of the unmanned surface vehicles is carried out to achieve the static collision avoidance. And in accordance with the Convention on the International Regulations for Preventing Collisions at Sea (COLREGS), a dynamic obstacle model is established and calculated to obtain the changes of the speed and course of the unmanned surface vehicles under different encounters. It is shown through the simulations that the proposed approach considering multiple factors can achieve the automatic collision avoidance.

Key concepts: Obstacle avoidance, Collision avoidance, Obstacle, Ant colony optimization algorithms, Computer science, Unmanned surface vehicle, Motion planning, Road surface

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