Metaheuristic Optimization for Mobile Robot Navigation Based爋n燩ath燩lanning

El-kenawy, El-Sayed M.; Khan, Zeeshan Shafi; Ibrahim, Abdelhameed; Aloyaydi, Bandar Abdullah; Ali, Hesham A.; Takieldeen, Ali E.

doi:10.32604/cmc.2022.026672

Cited by 2 publications

(1 citation statement)

References 18 publications

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“…Path planning involves determining continuous, optimized trajectories from the starting position to the target position [13], taking into account the constraints of the movement of robots [14] and obstacles in the environment. Global path planning focuses on planning on complete, known-environment maps to find the optimal route from the start point to the end point.…”

Section: Introductionmentioning

confidence: 99%

Research on preprocessing algorithm of indoor map partitioning and global path planning based on FAST

Yang,

Pan,

Liu

et al. 2023

Preprint

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Path planning is a critical factor in the successful performance of navigation tasks. This paper proposes a novel approach for indoor map partitioning and global path-planning preprocessing. The proposed algorithm aims to enhance the efficiency of path planning tasks by eliminating irrelevant areas. In view of the deformation problem encountered in the original indoor map partitioning method, initially, the contour detection algorithm is employed to identify and eliminate obstacles. Subsequently, the FAST algorithm is utilized to detect key points. These key points are then subjected to filtering and clustering using the K-means algorithm. Based on the 8-neighborhood characteristics, door points and inflection points within the room are selected. A clustering algorithm is employed to retain the door points, which are subsequently connected to form door line segments through averaging and filtering procedures. This process ensures the closure of the sub-room. Finally, the connected domain function is employed to extract the sub-room map, thereby completing the map partitioning process. Based on the sub-room map centroid coordinate point data obtained from the partitioning, two combinations are used as the starting point and the end point, respectively, and the A* algorithm is employed to calculate and store all path information from the starting point to the end point. Based on the sub-room map obtained through partitioning and the stored path information, the path is traversed to eliminate irrelevant areas, thereby achieving the preprocessing of global path planning. The simulation results showed that the A*, Bi-A*, JPS, Dijkstra, PRM, and RRT algorithms increased their rates by 18.2%, 43.6%, 20.5%, 31.9%, 29.1%, and 29.7%, respectively.

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Section: Introductionmentioning

confidence: 99%

Research on preprocessing algorithm of indoor map partitioning and global path planning based on FAST

Yang,

Pan,

Liu

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

Improved rapidly exploring random tree using salp swarm algorithm

Muhsen,

Raheem,

Sadiq

2024

Journal of Intelligent Systems

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Due to the limitations of the initial rapidly exploring random tree (RRT) algorithm, robotics faces challenges in path planning. This study proposes the integration of the metaheuristic salp swarm algorithm (SSA) to enhance the RRT algorithm, resulting in a new algorithm termed IRRT-SSA. The IRRT-SSA addresses issues inherent in the original RRT, enhancing efficiency and path-finding capabilities. A detailed explanation of IRRT-SSA is provided, emphasizing its distinctions from the core RRT. Comprehensive insights into parameterization and algorithmic processes contribute to a thorough understanding of its implementation. Comparative analysis demonstrates the superior performance of IRRT-SSA over the basic RRT, showing improvements of approximately 49, 54, and 54% in average path length, number of nodes, and number of iterations, respectively. This signifies the enhanced effectiveness of the proposed method. Theoretical and practical implications of IRRT-SSA are highlighted, particularly its influence on practical robotic applications, serving as an exemplar of tangible benefits.

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Metaheuristic Optimization for Mobile Robot Navigation Based爋n燩ath燩lanning

Cited by 2 publications

References 18 publications

Research on preprocessing algorithm of indoor map partitioning and global path planning based on FAST

Research on preprocessing algorithm of indoor map partitioning and global path planning based on FAST

Improved rapidly exploring random tree using salp swarm algorithm

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