Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Method for planning robot paths on basis of path expansion ant colony algorithms

A technology of path planning and ant colony algorithm, applied in navigation computing tools and other directions, can solve the problems of falling into local minima and low computing efficiency, and achieve the effect of high algorithm efficiency, strong search ability, and suppression of falling into local optimum.

Active Publication Date: 2016-12-14
UNIV OF SHANGHAI FOR SCI & TECH
View PDF5 Cites 61 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

These algorithms have their own advantages and disadvantages. For example, the artificial potential field method is simple and easy to implement, but it is easy to fall into a local minimum; the genetic algorithm has a good global solution ability, but the calculation efficiency is not high

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
  • Method for planning robot paths on basis of path expansion ant colony algorithms
  • Method for planning robot paths on basis of path expansion ant colony algorithms
  • Method for planning robot paths on basis of path expansion ant colony algorithms

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0034] When a robot walks in a complex working environment, it will be blocked by many obstacles of various shapes. The present invention uses the grid method to model the working environment of the robot to obtain a random map, such as figure 1 The grid map model diagram shown, in which the white grid is the free grid, which is the feasible area of ​​the robot, and the black grid is the obstacle grid, which is the area that the robot cannot pass. In order to describe the walking trajectory of the robot, figure 1 The medium unit grid is about the size of the robot. And code the rasters in the model from left to right and from top to bottom, and a raster represents a position node.

[0035] In the path optimization process, the ant colony algorithm is a search algorithm that simulates the behavior of ant colony foraging and finds the optimal path in a specified environment. Through research, it is found that when ants walk, they will release a special secretion - pheromone o...

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 relates to a method for planning robot paths on the basis of path expansion ant colony algorithms. The method has the advantages that the ant colony algorithms are applied to the field of robot path planning, path expansion ant colony algorithm optimization strategies are proposed, the robot path optimizing efficiency can be optimized, information element distribution time-varying characteristics, information element updating strategies, path location inflection point optimization and local optimal path expansion are introduced, and location inflection point parameters and general evaluation are additionally used as evaluation standards for the paths; as verified by simulation analysis and practical experiments on the three algorithms, the method is high in robot path planning and searching capacity on the basis of the path expansion ant colony algorithm optimization strategies and is high in algorithm efficiency, and the found paths are short; phenomena that the algorithms run into local optimization can be effectively inhibited, the optimal paths of robots can be searched, and the robots can quickly avoid obstacles to safely arrive at target points.

Description

technical field [0001] The invention relates to a path planning technology, in particular to a robot path planning method based on path expansion ant colony algorithm. Background technique [0002] Path planning technology is an important part of the research field of mobile robots. The main purpose is to find a path from the starting position node in the environment with obstacles according to certain criteria (such as the shortest path, the least position inflection point, the shortest time, etc.). The optimal or suboptimal safe collision-free path between nodes to the target location. Path planning can be divided into global path planning with completely known environment and local path planning with completely or partially unknown environment. [0003] Many feasible algorithms have been proposed for path planning at home and abroad, mainly including visual graph method, topology method, artificial potential field method and so on. In recent years, computational intelli...

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): G01C21/20
CPCG01C21/20
Inventor 甘屹曲凤挺孙福佳何伟铭焦会萌郑彬彬刘胜马新伍卢正钱程
Owner UNIV OF SHANGHAI FOR SCI & TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com