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Path Planning for Continuous-curvature Avoidance using Hierarchical Four Parameter Logistic Curves

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

3 Scopus citations

Abstract

Robots are widely used as unmanned vehicles in smart factories. In order to operate the robot in a known environment, the robot must be able to plan the path. The planned path must enable the robot to reach a destination from the starting point and the robot must avoid all obstacles during movement.This study uses a four-parameter logic curve path planning method that uses a closed formula solution and a curve with minimal design parameters to quickly generate an ideal path. The characteristics of the curve are used to derive the S and half-S curves as the solution path. The shortest path is used as the selection reference target to select parameters B and C for the four-parameter logic curve. For the S path, the best solution is chosen. The half -S curve is limited by the elastic end-point heading angle, which gives a unique set of parameter solutions. The generated path does not allow the robot to completely avoid obstacles so a hierarchical half-S curve path planning mechanism is used. A via point is generated at the collision point using the gradient vector for the edge of the obstacle. The planner continues to perform half-S path planning until the path planning ends.

Original languageEnglish
Title of host publication2020 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3358-3363
Number of pages6
ISBN (Electronic)9781728185262
DOIs
StatePublished - 11 Oct 2020
Event2020 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2020 - Toronto, Canada
Duration: 11 Oct 202014 Oct 2020

Publication series

NameConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
Volume2020-October
ISSN (Print)1062-922X

Conference

Conference2020 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2020
Country/TerritoryCanada
CityToronto
Period11/10/2014/10/20

Bibliographical note

Publisher Copyright:
© 2020 IEEE.

Keywords

  • obstacle avoidance
  • parameter logistic
  • path planning

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