Modified 2-Way Wavefront (M2W) Algorithm for Efficient Path Planning
In this paper modified 2-way wavefront algorithm(M2W) is introduced for the discretized path planning problem. The proposed scheme uses the Glasius model, wavefront navigational function, and adaptation of Artificial Potential Fields (APF) for effective obstacle avoidance. Unlike the APF, it does no...
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2021-03-01
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doaj-e36fe8ece509440897116177c03be1372021-03-25T09:45:57ZengAtlantis PressInternational Journal of Computational Intelligence Systems 1875-68832021-03-0114110.2991/ijcis.d.210305.002Modified 2-Way Wavefront (M2W) Algorithm for Efficient Path PlanningAyesha MaqboolAlina MirzaFarkhanda AfzalIn this paper modified 2-way wavefront algorithm(M2W) is introduced for the discretized path planning problem. The proposed scheme uses the Glasius model, wavefront navigational function, and adaptation of Artificial Potential Fields (APF) for effective obstacle avoidance. Unlike the APF, it does not suffer from local minima, and it addresses the shortcoming of the navigational method by generating paths that are not “too close” to obstacles. Furthermore, compared to the Glasius model, M2W's computation time is significantly reduced, especially in a complex workspace with a higher density of obstacles. The proposed algorithm is also simulated with an additional set of planning constraints to demonstrate the adaptability of the M2W for constraint planning problems.https://www.atlantis-press.com/article/125954090/viewRobotic path planningSafe path generationWavefront algorithmsSelf-organizing mapsArtificial potential fieldsNavigational function |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ayesha Maqbool Alina Mirza Farkhanda Afzal |
spellingShingle |
Ayesha Maqbool Alina Mirza Farkhanda Afzal Modified 2-Way Wavefront (M2W) Algorithm for Efficient Path Planning International Journal of Computational Intelligence Systems Robotic path planning Safe path generation Wavefront algorithms Self-organizing maps Artificial potential fields Navigational function |
author_facet |
Ayesha Maqbool Alina Mirza Farkhanda Afzal |
author_sort |
Ayesha Maqbool |
title |
Modified 2-Way Wavefront (M2W) Algorithm for Efficient Path Planning |
title_short |
Modified 2-Way Wavefront (M2W) Algorithm for Efficient Path Planning |
title_full |
Modified 2-Way Wavefront (M2W) Algorithm for Efficient Path Planning |
title_fullStr |
Modified 2-Way Wavefront (M2W) Algorithm for Efficient Path Planning |
title_full_unstemmed |
Modified 2-Way Wavefront (M2W) Algorithm for Efficient Path Planning |
title_sort |
modified 2-way wavefront (m2w) algorithm for efficient path planning |
publisher |
Atlantis Press |
series |
International Journal of Computational Intelligence Systems |
issn |
1875-6883 |
publishDate |
2021-03-01 |
description |
In this paper modified 2-way wavefront algorithm(M2W) is introduced for the discretized path planning problem. The proposed scheme uses the Glasius model, wavefront navigational function, and adaptation of Artificial Potential Fields (APF) for effective obstacle avoidance. Unlike the APF, it does not suffer from local minima, and it addresses the shortcoming of the navigational method by generating paths that are not “too close” to obstacles. Furthermore, compared to the Glasius model, M2W's computation time is significantly reduced, especially in a complex workspace with a higher density of obstacles. The proposed algorithm is also simulated with an additional set of planning constraints to demonstrate the adaptability of the M2W for constraint planning problems. |
topic |
Robotic path planning Safe path generation Wavefront algorithms Self-organizing maps Artificial potential fields Navigational function |
url |
https://www.atlantis-press.com/article/125954090/view |
work_keys_str_mv |
AT ayeshamaqbool modified2waywavefrontm2walgorithmforefficientpathplanning AT alinamirza modified2waywavefrontm2walgorithmforefficientpathplanning AT farkhandaafzal modified2waywavefrontm2walgorithmforefficientpathplanning |
_version_ |
1724203680206422016 |