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Trudy SPIIRAN, 2019, Issue 18, volume 1, Pages 57–84
DOI: https://doi.org/10.15622/sp.18.1.57-84
(Mi trspy1039)
 

This article is cited in 28 scientific papers (total in 28 papers)

Artificial Intelligence, Knowledge and Data Engineering

Development and implementation of spline-based path planning algorithm in ROS/Gazebo environment

R. O. Lavrenova, E. A. Magida, F. Matsunob, M. M. Svininc, J. Suthakornd

a Kazan Federal University
b Kyoto University
c Ritsumeikan University
d Mahidol University
Abstract: Path planning for autonomous mobile robots is an important task within robotics field. It is common to use one of the two classical approaches in path planning: a global approach when an entire map of a working environment is available for a robot or local methods, which require the robot to detect obstacles with a variety of onboard sensors as the robot traverses the environment.
In our previous work, a multi-criteria spline algorithm prototype for a global path construction was developed and tested in Matlab environment. The algorithm used the Voronoi graph for computing an initial path that serves as a starting point of the iterative method. This approach allowed finding a path in all map configurations whenever the path existed. During the iterative search, a cost function with a number of different criteria and associated weights was guiding further path optimization. A potential field method was used to implement some of the criteria.
This paper describes an implementation of a modified spline-based algorithm that could be used with real autonomous mobile robots. Equations of the characteristic criteria of a path optimality were further modified. The obstacle map was previously presented as intersections of a finite number of circles with various radii. However, in real world environments, obstacles’ data is a dynamically changing probability map that could be based on an occupancy grid. Moreover, the robot is no longer a geometric point.
To implement the spline algorithm and further use it with real robots, the source code of the Matlab environment prototype was transferred into C++ programming language. The testing of the method and the multi criteria cost function optimality was carried out in ROS/Gazebo environment, which recently has become a standard for programming and modeling robotic devices and algorithms.
The resulting spline-based path planning algorithm could be used on any real robot, which is equipped with a laser rangefinder. The algorithm operates in real time and the influence of the objective function criteria parameters are available for dynamic tuning during a robot motion.
Keywords: path planning, mobile robot, planning algorithm, ROS, Gazebo, spline-based algorithm.
Funding agency Grant number
Russian Foundation for Basic Research 19-58-70002
This research is supported by RFBR (project No. 19-58-70002).
Received: 28.01.2019
Bibliographic databases:
Document Type: Article
UDC: 007.52, 519.878, 519.1, 004.942, 006.72
Language: Russian
Citation: R. O. Lavrenov, E. A. Magid, F. Matsuno, M. M. Svinin, J. Suthakorn, “Development and implementation of spline-based path planning algorithm in ROS/Gazebo environment”, Tr. SPIIRAN, 18:1 (2019), 57–84
Citation in format AMSBIB
\Bibitem{LavMagMat19}
\by R.~O.~Lavrenov, E.~A.~Magid, F.~Matsuno, M.~M.~Svinin, J.~Suthakorn
\paper Development and implementation of spline-based path planning algorithm in ROS/Gazebo environment
\jour Tr. SPIIRAN
\yr 2019
\vol 18
\issue 1
\pages 57--84
\mathnet{http://mi.mathnet.ru/trspy1039}
\crossref{https://doi.org/10.15622/sp.18.1.57-84}
\elib{https://elibrary.ru/item.asp?id=37286132}
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  • https://www.mathnet.ru/eng/trspy/v18/i1/p57
  • This publication is cited in the following 28 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
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