Optimizing the A*algorithm for remote sensing image path planning
To address the challenges when conducting path planning on high-resolution remote sensing images,such as the extensive search space,reduced efficiency,and increased number of turning points,this paper proposes a global path planning algorithm based on the A*algorithm.First,a cosine function is introduced into the heuristic function of the original A*algorithm to minimize the search process of redundant nodes and narrow down the search scope,thereby enhancing the algorithm's operational efficiency.Then,a turning point optimization scheme is designed to reduce unnecessary turning points in the planned path,improving the smoothness of the path planning results.Finally,to validate the effectiveness of the proposed algorithm,simulation experiments are conducted in Matlab software.Our study compares the search node scope and the number of turning points between the original A*algorithm and the enhanced one.Meanwhile,a comparative experiment is performed employing binary maps derived from remote sensing images to analyze the path length and execution time.Our experimental data indicate the enhanced algorithm reduces expansion nodes by over 30％and non-essential turning points by over 35％.Moreover,it shortens the path planning length by 15.5％and decreases the running time by 12.5％,demonstrating a higher efficiency in seeking the optimal paths.
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