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DVG+A* and RRT Path-Planners: A Comparison in a Highly Dynamic Environment

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Abstract

This work provides a deeper comparison between two path planning algorithms, the Dynamic Visibility Graph A Star (DVG+A*) and Rapidly–exploring Random Trees (RRT), when applied in a high dimension and dynamic environment, which is the RoboCup Small Size League. The algorithms were compared under two different perspectives. In the first analysis, the algorithms were evaluated according to its computational time, path length and path safety in a static environment. Afterwards, they were evaluated regarding the accumulated computational time, number of recalculated paths, total navigation time and number of collisions in a dynamic environment. The static environment results have shown that the DVG+A* has a better overall performance than RRT, except for the path safety, however, some ideas on how to improve this were discussed. In the dynamic environment the algorithms performed similarly and with a high number of collisions during the experiments. Thus, showing the importance of using an obstacle avoidance algorithm combined with the path planner. In conclusion, the results obtained showed that both algorithms aren’t suitable for highly dynamic and cluttered environments, however, due how sparse the obstacles are in the SSL, they can still be used with some care. Regarding static environments, the DVG+A* has shown the best results.

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The authors confirm that the data supporting the findings of this study are available within this article and in the following repository: https://bit.ly/34IM5qe. All images shown in the article were made by the authors and can also be found at the repository.

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Funding

This work was supported by University Center of FEI and it is based on a scientific project on mobile robots under funding number PBIC133/17.

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Authors and Affiliations

  1. Department of Control and Automation Engineering, University Center of FEI, São Bernardo do Campo, SP, Brazil

    Leonardo da Silva Costa

  2. Department of Computer Science, University Center of FEI, São Bernardo do Campo, SP, Brazil

    Flavio Tonidandel

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  1. Leonardo da Silva Costa
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  2. Flavio Tonidandel
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Contributions

Leonardo da Silva Costa implemented the algorithms, designed and performed the experiments, analyzed the data and wrote the manuscript. Flavio Tonidandel provided critical feedback, supervised and shaped the project, research, analysis and manuscript.

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Correspondence to Leonardo da Silva Costa.

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This work was supported by University Center of FEI.

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da Silva Costa, L., Tonidandel, F. DVG+A* and RRT Path-Planners: A Comparison in a Highly Dynamic Environment. J Intell Robot Syst 101, 58 (2021). https://doi.org/10.1007/s10846-021-01326-0

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