A Comprehensive Study of Recent Path-Planning Techniques in Dynamic Environments for Autonomous Robots

This paper presents a comprehensive review of path planning in dynamic environments. This review covers the entire process, starting from obstacle detection techniques, through path-planning strategies, and also extending to formation control and communication styles. The review discusses the key trends, challenges, and gaps in current methods to emphasize the need for more efficient and robust algorithms that can handle complex and unpredictable dynamic environments. Moreover, it discusses the importance of collaborative decision making and communication between robots to optimize path planning in dynamic scenarios. This work serves as a valuable resource for advancing research and practical applications in dynamic obstacle navigation.

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Publication Details

Journal
Sensors
Published
2024-12-18
DOI
https://doi.org/10.3390/s24248089
Citations
33
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
8.22
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article

A Comprehensive Study of Recent Path-Planning Techniques in Dynamic Environments for Autonomous Robots

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Sensors
Robotic Path Planning Algorithms
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article

A Comprehensive Study of Recent Path-Planning Techniques in Dynamic Environments for Autonomous Robots

Maâmar Bettayeb, Mohammed Baziyad, Raouf Fareh, Nour Ayman Abujabal, Tamer Rabie, Brahim Brahmi
article en
33 citations

Abstract

This paper presents a comprehensive review of path planning in dynamic environments. This review covers the entire process, starting from obstacle detection techniques, through path-planning strategies, and also extending to formation control and communication styles. The review discusses the key trends, challenges, and gaps in current methods to emphasize the need for more efficient and robust algorithms that can handle complex and unpredictable dynamic environments. Moreover, it discusses the importance of collaborative decision making and communication between robots to optimize path planning in dynamic scenarios. This work serves as a valuable resource for advancing research and practical applications in dynamic obstacle navigation.

SensorsVol. 24(24)
College Ahuntsic (CA), University of Sharjah (AE)
Peace, Justice and strong institutions
Openalex Percentile: Top 2%
Robotic Path Planning Algorithms
8.22
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