Border Inspection Path Planning Based on Improved Grey Wolf Optimizer

This article proposes a border inspection path planning method based on the improved Grey Wolf Optimizer(GWO). This method adds a fourth layer of Grey Wolf search and introduces a new decision layer in the original algorithm, which can expand the search range and reduce the probability of local optima. It can effectively plan border inspection paths and improve inspection efficiency. This article elaborates on the implementation process of the improved GWO and verifies its effectiveness and superiority through experiments. The experimental results show that the improved GWO has better path planning effectiveness and performance evaluation compared to traditional GWO and genetic algorithms. The research results of this article have certain practical application value for optimizing border inspection path planning.