Simulation-based review of classical, heuristic, and metaheuristic path planning algorithms

Abstract Path planning is the process by which an autonomous robot obtains information about its environment and chooses the best route from the start point to the target destination while avoiding obstacles. It is vital to the success of robot operation as it provides autonomous maneuverability wit...

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Main Authors: Kenneth Christopher Ugwoke, Nwojo Agwu Nnanna, Saleh El-Yakub Abdullahi
Format: Article
Language:English
Published: Nature Portfolio 2025-04-01
Series:Scientific Reports
Subjects:
Online Access:https://doi.org/10.1038/s41598-025-96614-2
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author Kenneth Christopher Ugwoke
Nwojo Agwu Nnanna
Saleh El-Yakub Abdullahi
author_facet Kenneth Christopher Ugwoke
Nwojo Agwu Nnanna
Saleh El-Yakub Abdullahi
author_sort Kenneth Christopher Ugwoke
collection DOAJ
description Abstract Path planning is the process by which an autonomous robot obtains information about its environment and chooses the best route from the start point to the target destination while avoiding obstacles. It is vital to the success of robot operation as it provides autonomous maneuverability within the environment, ensuring a collision-free and optimum path that guarantees efficient movement. This paper introduces and categorizes several notable path-planning algorithms used in robotics operations. We delve into their basic principles, key features, challenges, and real-world applications. Additionally, we provided a simulated comparison result of the notable path-planning algorithms. Finally, we analyze the outcomes, give a concise conclusion, and forecast the future trends in path planning techniques.
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spelling doaj-art-f66f033ed5064c6bb51ea9d3cd49ccdb2025-08-20T02:11:41ZengNature PortfolioScientific Reports2045-23222025-04-0115113610.1038/s41598-025-96614-2Simulation-based review of classical, heuristic, and metaheuristic path planning algorithmsKenneth Christopher Ugwoke0Nwojo Agwu Nnanna1Saleh El-Yakub Abdullahi2Department of Computer Science, Nile University of NigeriaDepartment of Computer Science, Nile University of NigeriaDepartment of Computer Science, Nile University of NigeriaAbstract Path planning is the process by which an autonomous robot obtains information about its environment and chooses the best route from the start point to the target destination while avoiding obstacles. It is vital to the success of robot operation as it provides autonomous maneuverability within the environment, ensuring a collision-free and optimum path that guarantees efficient movement. This paper introduces and categorizes several notable path-planning algorithms used in robotics operations. We delve into their basic principles, key features, challenges, and real-world applications. Additionally, we provided a simulated comparison result of the notable path-planning algorithms. Finally, we analyze the outcomes, give a concise conclusion, and forecast the future trends in path planning techniques.https://doi.org/10.1038/s41598-025-96614-2Path planningMobile robotAlgorithmMetaheuristicCollision-free path
spellingShingle Kenneth Christopher Ugwoke
Nwojo Agwu Nnanna
Saleh El-Yakub Abdullahi
Simulation-based review of classical, heuristic, and metaheuristic path planning algorithms
Scientific Reports
Path planning
Mobile robot
Algorithm
Metaheuristic
Collision-free path
title Simulation-based review of classical, heuristic, and metaheuristic path planning algorithms
title_full Simulation-based review of classical, heuristic, and metaheuristic path planning algorithms
title_fullStr Simulation-based review of classical, heuristic, and metaheuristic path planning algorithms
title_full_unstemmed Simulation-based review of classical, heuristic, and metaheuristic path planning algorithms
title_short Simulation-based review of classical, heuristic, and metaheuristic path planning algorithms
title_sort simulation based review of classical heuristic and metaheuristic path planning algorithms
topic Path planning
Mobile robot
Algorithm
Metaheuristic
Collision-free path
url https://doi.org/10.1038/s41598-025-96614-2
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AT nwojoagwunnanna simulationbasedreviewofclassicalheuristicandmetaheuristicpathplanningalgorithms
AT salehelyakubabdullahi simulationbasedreviewofclassicalheuristicandmetaheuristicpathplanningalgorithms