DistBug path planning algorithm package for ROS Noetic

DOI

Description

Algorithms of path-planning in an unknown environment play an important role in robotics. They do not require a prior information about obstacles' locations around a robot and allow calculating a path in a real time. This article presents an implementation of a sensory-based DistBug algorithm, which operates reactively using range data for immediate decision-making without constructing a world model. The algorithm was programmed in Python using robot operating system (ROS) and validated in the Gazebo simulator. For virtual experiments Turtlebot 3 Burger mobile robot was employed. The experiments were conducted in two types of environment: an environment with convex obstacles and a maze. The paper demonstrates analysis of experiments using several standard criteria of a path quality estimation.

Journal

Keywords

Details 詳細情報について

  • CRID
    1390581456538579584
  • DOI
    10.5954/icarob.2024.os10-5
  • ISSN
    21887829
  • Text Lang
    en
  • Data Source
    • JaLC
    • Crossref
  • Abstract License Flag
    Disallowed

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