Robot path planning for human search in indoor environments

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Aiming at the problem of a mobile robot searching human in home environments, a gird model is built and a path planning method based on a modified genetic algorithm and an improved A* algorithm is proposed. First, the grid map is divided into several unit regions using Boustrophedon cellular decomposition. Then, a unit region planning method based on a genetic algorithm is applied to generate a region transition sequence, and an effective strategy to search every region is adjusted according to the robot’s sensors. Meanwhile, the optimal path between two points is generated by an improved A* algorithm, so that the path is much shorter and the number of turns is greatly reduced. Finally, the simulation results verify that this method can provide an optimized path in known home environments effectively, based on that the robot can find human in the shortest possible time.

Original languageEnglish
Title of host publicationCognitive Systems and Signal Processing - 3rd International Conference, ICCSIP 2016, Revised Selected Papers
EditorsFuchun Sun, Huaping Liu, Dewen Hu
PublisherSpringer Verlag
Pages310-323
Number of pages14
ISBN (Print)9789811052293
DOIs
StatePublished - 2017
Externally publishedYes
Event3rd International Conference on Cognitive Systems and Information Processing, ICCSIP 2016 - Beijing, China
Duration: 19 Nov 201623 Nov 2016

Publication series

NameCommunications in Computer and Information Science
Volume710
ISSN (Print)1865-0929

Conference

Conference3rd International Conference on Cognitive Systems and Information Processing, ICCSIP 2016
Country/TerritoryChina
CityBeijing
Period19/11/1623/11/16

Keywords

  • A* algorithm
  • Genetic algorithm
  • Grid method
  • Indoor mobile robot
  • Path planning

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