Obstacle Avoidance Using Safe Dynamic Window Approach for Mobile Robot

This paper proposes a Safe Dynamic Window Approach (SDWA) as an extension of the classical Dynamic Window Approach (DWA) to incorporate the Threat Level Index in order to insert safety and comfort criteria into human-robot interaction. SDWA takes into account both static and dynamic obstacles while ensuring safety and comfort distances whenever the TLI threshold values are 0.46 for safety and 0.29 for comfort. The results of the simulation reveal that SDWA is able to keep the TLI value constantly below 0.29, while the original DWA reached a maximum of 0.63, which means risk may occur. In addition, it can be seen that the navigation task accomplished by SDWA in 508’s is approximately twice as fast as the original DWA, which takes 1142’s to complete the same task. Accordingly, validation of the improvement capability of SDWA related to robot trajectory optimization with a guarantee on safety and comfort in dynamic interaction is performed.

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Publication Details

Published
2024-12-11
DOI
https://doi.org/10.1109/isriti64779.2024.10963513
Citations
2
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
0.50
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article

Obstacle Avoidance Using Safe Dynamic Window Approach for Mobile Robot

Trihastuti Agustinah, Yurid Nugraha, Lena Susianti
2 citations
Robotic Path Planning Algorithms
0.50
article

Obstacle Avoidance Using Safe Dynamic Window Approach for Mobile Robot

Trihastuti Agustinah, Yurid Nugraha, Lena Susianti
article en
2 citations

Abstract

This paper proposes a Safe Dynamic Window Approach (SDWA) as an extension of the classical Dynamic Window Approach (DWA) to incorporate the Threat Level Index in order to insert safety and comfort criteria into human-robot interaction. SDWA takes into account both static and dynamic obstacles while ensuring safety and comfort distances whenever the TLI threshold values are 0.46 for safety and 0.29 for comfort. The results of the simulation reveal that SDWA is able to keep the TLI value constantly below 0.29, while the original DWA reached a maximum of 0.63, which means risk may occur. In addition, it can be seen that the navigation task accomplished by SDWA in 508’s is approximately twice as fast as the original DWA, which takes 1142’s to complete the same task. Accordingly, validation of the improvement capability of SDWA related to robot trajectory optimization with a guarantee on safety and comfort in dynamic interaction is performed.

Sepuluh Nopember Institute of Technology (ID)
Openalex Percentile: Top 32%
Robotic Path Planning Algorithms
0.50
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