Unmanned surface vehicle collision avoidance method based on genetic algorithm and particle swarm optimization algorithm

A technology of particle swarm algorithm and genetic algorithm, which is applied in the field of collision avoidance of unmanned boats in maritime intelligent transportation technology, can solve problems such as path planning and calculation without avoidance

Active Publication Date: 2019-06-25
HARBIN ENG UNIV
View PDF6 Cites 14 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The patent application number is CN201610942213.5, an unmanned boat collision avoidance method based on the improved ant colony algorithm, which uses the improved ant colony algorithm to plan the safe route of the unmanned boat. This method has certain limitations and does not target Calculation of avoidance path planning for static and dynamic obstacles

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Unmanned surface vehicle collision avoidance method based on genetic algorithm and particle swarm optimization algorithm
  • Unmanned surface vehicle collision avoidance method based on genetic algorithm and particle swarm optimization algorithm
  • Unmanned surface vehicle collision avoidance method based on genetic algorithm and particle swarm optimization algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0085] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and understandable, the present invention will be further described below in conjunction with the accompanying drawings:

[0086] Technical scheme of the present invention is realized like this:

[0087] 1. Research on the relevant parameters and collision avoidance constraint rules in path planning and collision avoidance of unmanned vehicles:

[0088] The mathematical model parameters of the motion of the unmanned boat involve the position and speed of the unmanned boat and the position and speed of obstacles. The relative speed, relative position and relative orientation motion parameters of the two derived from this. Four different collision situations of unmanned vehicle and obstacle, frontal obstacle avoidance, overrun obstacle avoidance, right chord crossing and left chord crossing obstacle avoidance are summarized. The restraint rules for collision avoida...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention belongs to the field of unmanned surface vehicle avoidance in maritime intelligent transportation technologies and relates to an unmanned surface vehicle collision avoidance method basedon a genetic algorithm and a particle swarm optimization algorithm. The method includes the following steps that: related parameters and collision avoidance constraint rules in unmanned surface vehicle collision avoidance path planning are studied; a path for an unmanned surface vehicle to avoid a static obstacle is planned the basis of the genetic algorithm; and the genetic algorithm and the particle swarm optimization algorithm are combined to perform dynamic collision avoidance path planning, and therefore, path optimization can be completed, a feasible collision avoidance path can be outputted, and the navigation of the unmanned surface vehicle is resumed. Compared with a traditional unmanned surface vehicle collision avoidance technology, the method of the invention can obtain optimal path planning, accurately avoid collision, and ensure that the unmanned surface vehicle can safely reach a target point.

Description

technical field [0001] The invention relates to the field of collision avoidance of unmanned boats in maritime intelligent transportation technology, in particular to a collision avoidance method for unmanned boats based on genetic algorithm and particle swarm algorithm. Background technique [0002] Unmanned Vehicle (USV) is a small water surface sports platform that integrates autonomous planning, autonomous navigation, autonomous environmental perception, and target detection. It has become an indispensable device for exploring marine resources. [0003] Path planning and collision avoidance are the key to autonomous navigation of unmanned boats. Therefore, before the unmanned boat enters the waters to perform tasks, it is necessary to plan a full navigation route based on the known hydrological data of the sea area. Due to the complex and changeable ocean environment, it is impossible to predict what will happen during the voyage, such as encountering strong winds and w...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G05D1/02
Inventor 林孝工刘叶叶刘向波王汝珣杨荣浩刘志宇郭如鑫
Owner HARBIN ENG UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap