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

Multi-robot full-coverage task allocation method

A task allocation and multi-robot technology, applied in the field of task allocation based on genetic algorithm, can solve the problem that the allocation method cannot obtain a higher quality approximate optimal solution

Active Publication Date: 2018-01-09
NAT UNIV OF DEFENSE TECH
View PDF7 Cites 11 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0012] The technical problem to be solved by the present invention is to assign a multi-robot full-coverage task. The traditional assignment method cannot obtain a higher-quality approximate optimal solution, and is only applicable to a smaller graph scale and a smaller number of blocks. Case

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
  • Multi-robot full-coverage task allocation method
  • Multi-robot full-coverage task allocation method
  • Multi-robot full-coverage task allocation method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0075] figure 1 It is a schematic diagram of the two-dimensional modeling of the real environment constructed by the present invention. Such as figure 1 as shown, figure 1 It is a modeling of a real environment. M1-M5 respectively represent Morse points, vertical lines represent Morse straight lines, R1, R2, R3, R4, R6, R7, R8, R9 represent small regions drawn by Morse straight lines from the entire large region. A possible 3-partition is {{R1}, {R2, R3, R4, R6, R7}, {R5, R6, R8, R9}}.

[0076] figure 2 It is the overall flowchart of the present invention. image 3 (a) is an example of a real full-coverage environment, which is used to illustrate the specific implementation manner of the present invention. image 3 (a) The environment shown is a closed room, and the thick black frame represents the wall, which is impassable; image 3 (b) is image 3 (a) The original topological map; image 3 (c) is based on image 3 (b) A random tree that may be generated.

[0077]...

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 discloses a multi-robot full-coverage task allocation method. The technical scheme includes the steps of first performing decomposition modeling on a full-coverage environment to obtaina topological graph G, and based on G, generating a pop directed generation trees, i.e., individuals, as the 0th generation of population; adopting an individual adaptation calculation method to calculate adaptation of T1, T2,..., Tk.., Tpop separately according to the number of blocks q into which G is to be segmented; finding the individual best with the lowest adaptation and the individual worst with the highest adaptation; and iterating maxgen generations, each generation using selection crossover and mutation operators to select potential individuals and generate more potential individuals, adopting an individual adaption calculation method to calculate the adaptation of individuals of the (maxgen)th generation, and recording an obtained a cutting scheme in the calculation process. Byadoption of the multi-robot full-coverage task allocation method, only a relatively small population and a relatively small evolution generation number are needed to obtain an approximate solution which is very close to an optimal solution.

Description

technical field [0001] The invention relates to a task allocation method before multi-robots perform full-coverage tasks, in particular to a task allocation method based on a genetic algorithm. Background technique [0002] The full coverage task refers to the use of mobile robots to traverse the target environment area within the range of physical contact or sensor perception, and to meet the goals of short time, less repeated paths or small untraversed areas as much as possible. Full coverage technology is the basis for many robot applications, such as floor cleaning, oil cleaning, grass mowing, grain harvesting, seabed exploration, mine clearance, etc. Multi-robot full-coverage tasks have two most important steps—task assignment and path planning. The present invention relates to a method for multi-robots to perform full-coverage task assignment. [0003] The full coverage environment needs to be modeled prior to task assignment. Since the full coverage environment is ...

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
IPC IPC(8): G06Q10/06G06N3/12
Inventor 刘惠王怀民丁博周星史佩昌胡奔李艺颖包慧尚苏宁
Owner NAT UNIV OF DEFENSE 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