Modified Spline-based Path Planning for Autonomous Ground Vehicle

Evgeni Magid, Roman Lavrenov, Airat Khasianov

2017

Abstract

Potential function based methods play significant role in global and local path planning. While these methods are characterized with good reactive behavior and implementation simplicity, they suffer from a well-known problem of getting stuck in local minima of a navigation function. In this article we propose a modification of our original spline-based path planning algorithm for a mobile robot navigation, which succeeds to solve local minima problem and adds additional criteria of start and target points visibility to help optimizing the path selection. We apply a Voronoi graph based path as an input for iterative multi criteria optimization algorithm. The algorithm was implemented in Matlab environment and simulation results demonstrate that we succeeded to overcome our original algorithm pitfalls.

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Paper Citation


in Harvard Style

Magid E., Lavrenov R. and Khasianov A. (2017). Modified Spline-based Path Planning for Autonomous Ground Vehicle . In Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO, ISBN 978-989-758-264-6, pages 132-141. DOI: 10.5220/0006442601320141


in Bibtex Style

@conference{icinco17,
author={Evgeni Magid and Roman Lavrenov and Airat Khasianov},
title={Modified Spline-based Path Planning for Autonomous Ground Vehicle},
booktitle={Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,},
year={2017},
pages={132-141},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006442601320141},
isbn={978-989-758-264-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,
TI - Modified Spline-based Path Planning for Autonomous Ground Vehicle
SN - 978-989-758-264-6
AU - Magid E.
AU - Lavrenov R.
AU - Khasianov A.
PY - 2017
SP - 132
EP - 141
DO - 10.5220/0006442601320141