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June 4, 2026AlgorithmsOpen Access

Unmanned Ground Vehicle Path Planning Algorithms: A Review

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Review analyzes path planning algorithms for unmanned ground vehicles and suggests enhancements for real-world use.

This review focuses on evaluating various path planning algorithms for unmanned ground vehicles to improve their navigation capabilities.
Classified path planning algorithms into six types: graph-search-based, sampling-based, local optimization-based, meta-heuristic optimization, AI-based, and optimal control methods.
Conducted bibliometric analysis to identify research trends and gaps in current methodologies.
Discussed improvements and limitations of each algorithm type for real-world applications.
Identified significant gaps in current research regarding the reliance on simulation methods and restrictive environmental assumptions.
Emphasized the challenges of multi-objective optimization and the need for hybrid algorithms to enhance performance.
Advocated for improved validation processes in real environments for better practical applications.

Ma et al. (2026) studied this question.

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