Improved adaptive wind driven optimization algorithm for real-time path planning

Description

Recently, path planning has achieved remarkable progress in enhancing global search capability and convergence accuracy through heuristic and learning-inspired optimization frameworks. However, real-time adaptability in dynamic environments remains a critical challenge for autonomous navigation, particularly when robots must generate collision-free, smooth, and efficient trajectories under complex constraints. By analyzing the difficulties in dynamic path planning, the Wind Driven Optimization (

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