OGPR:: An Obstacle-Guided Path Refinement Approach for Mobile Robot Path Planning

M.G.B. Atia; O. Salah; H. Ei-Hussieny

doi:10.1109/ROBIO.2018.8665080

OGPR: An Obstacle-Guided Path Refinement Approach for Mobile Robot Path Planning

M.G.B. Atia
, O. Salah
, H. Ei-Hussieny

EEE - Academic & Research

Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

Abstract

Despite the emergence of the available path planning approaches for mobile robots, excessive computation time have remained an open issue, especially in time-critical scenarios. In this paper, however, an Obstacle-Guided Path Refinement (OGPR) approach is developed to plan a set of short collision-free paths between the start and the target points for mobile robots. A particle swarm optimization framework has been adopted to retrieve the obstacles geometry and subsequently refine the line-of-sight path connecting the start and the target points. The developed OGPR approach has assessed over a 2D simulation environment and the results show that its effectiveness in planning safe paths shorter than the state-of-the-art A* algorithm. This, in fact, could encourage further application of the proposed OGPR approach in future in 3D spatial environments.

Original language	Undefined
Title of host publication	2018 IEEE International Conference on Robotics and Biomimetics, ROBIO 2018
DOIs	https://doi.org/10.1109/ROBIO.2018.8665080
Publication status	Published - 2018

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10.1109/ROBIO.2018.8665080

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@inproceedings{b25d2e46c00c4b7e9f046dafb442b602,

title = "OGPR:: An Obstacle-Guided Path Refinement Approach for Mobile Robot Path Planning",

abstract = "Despite the emergence of the available path planning approaches for mobile robots, excessive computation time have remained an open issue, especially in time-critical scenarios. In this paper, however, an Obstacle-Guided Path Refinement (OGPR) approach is developed to plan a set of short collision-free paths between the start and the target points for mobile robots. A particle swarm optimization framework has been adopted to retrieve the obstacles geometry and subsequently refine the line-of-sight path connecting the start and the target points. The developed OGPR approach has assessed over a 2D simulation environment and the results show that its effectiveness in planning safe paths shorter than the state-of-the-art A* algorithm. This, in fact, could encourage further application of the proposed OGPR approach in future in 3D spatial environments.",

author = "M.G.B. Atia and O. Salah and H. Ei-Hussieny",

year = "2018",

doi = "10.1109/ROBIO.2018.8665080",

language = "Undefined",

booktitle = "2018 IEEE International Conference on Robotics and Biomimetics, ROBIO 2018",

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T1 - OGPR:

T2 - An Obstacle-Guided Path Refinement Approach for Mobile Robot Path Planning

AU - Atia, M.G.B.

AU - Salah, O.

AU - Ei-Hussieny, H.

PY - 2018

Y1 - 2018

N2 - Despite the emergence of the available path planning approaches for mobile robots, excessive computation time have remained an open issue, especially in time-critical scenarios. In this paper, however, an Obstacle-Guided Path Refinement (OGPR) approach is developed to plan a set of short collision-free paths between the start and the target points for mobile robots. A particle swarm optimization framework has been adopted to retrieve the obstacles geometry and subsequently refine the line-of-sight path connecting the start and the target points. The developed OGPR approach has assessed over a 2D simulation environment and the results show that its effectiveness in planning safe paths shorter than the state-of-the-art A* algorithm. This, in fact, could encourage further application of the proposed OGPR approach in future in 3D spatial environments.

AB - Despite the emergence of the available path planning approaches for mobile robots, excessive computation time have remained an open issue, especially in time-critical scenarios. In this paper, however, an Obstacle-Guided Path Refinement (OGPR) approach is developed to plan a set of short collision-free paths between the start and the target points for mobile robots. A particle swarm optimization framework has been adopted to retrieve the obstacles geometry and subsequently refine the line-of-sight path connecting the start and the target points. The developed OGPR approach has assessed over a 2D simulation environment and the results show that its effectiveness in planning safe paths shorter than the state-of-the-art A* algorithm. This, in fact, could encourage further application of the proposed OGPR approach in future in 3D spatial environments.

UR - https://www.scopus.com/pages/publications/85064116922

U2 - 10.1109/ROBIO.2018.8665080

DO - 10.1109/ROBIO.2018.8665080

M3 - Conference contribution

BT - 2018 IEEE International Conference on Robotics and Biomimetics, ROBIO 2018

ER -

OGPR: An Obstacle-Guided Path Refinement Approach for Mobile Robot Path Planning

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