多障礙環境下巡檢機器人路徑規劃優化研究

摘" 要： 針對大規模、密集的障礙物分布，高效地搜索最佳路徑是一個挑戰，為規劃出更短的巡檢路線，并實現多障礙環境下的靈活避障，文中提出一種多障礙環境下巡檢機器人路徑規劃優化方法。使用二維矩陣構建巡檢環境模型，應用D*算法在巡檢環境模型中進行巡檢機器人路徑規劃，并將傳統D*算法中的擴展步長方式改變為自適應擴展步長，使機器人在面積較大的巡檢場地能夠更快地完成巡檢；將代價函數由歐氏距離替換為切比雪夫諾距離和曼哈頓距離融合的代價函數，并引入了平滑度函數優化線路規劃結果，使規劃的路徑更為平滑，在遇到由于多種原因產生的新障礙物時可以重新規劃路徑。通過實驗結果可知，無論是靜態地圖還是動態地圖，該方法均可以快速準確地規劃出一條最佳路線，并且在多種環境中應用該方法能夠高效獲取路徑規劃結果。

關鍵詞： 多障礙； 巡檢機器人； 路徑規劃； D*算法； 動態環境； 擴展節點； 代價函數； 擴展步長

中圖分類號： TN911?34； TP391" " " " " " " " " " "文獻標識碼： A" " " " " " " " " " 文章編號： 1004?373X（2025）01?0130?05

Research on path planning optimization of inspection robot"in multi?obstacle environment

QIAO Daoji1， ZHANG Yanbing2

（1. School of Computer Science and Technology， North University of China， Taiyuan 030051， China;

2. School of Electrical and Control Engineering， North University of China， Taiyuan 030051， China）

Abstract： In the case of the large?scale and dense obstacle distributions， it is a challenge to search the best path efficiently. In order to get shorter inspection routes and achieve flexible obstacle avoidance in multi?obstacle environments， a research on path planning optimization methods for inspection robots in multi?obstacle environments is carried out. An inspection environment model is constructed by a two?dimensional matrix. The D* algorithm is applied to plan the path of the inspection robot in the inspection environment model. The means of the extended step size in the traditional D* algorithm is changed to adaptive extended step size， so that the robot can complete inspections faster in larger inspection sites. The cost function is replaced by the one based on the fusion of Chebyshev distance and Manhattan distance. The smoothness function is introduced to optimize the route planning results， which makes the planned path smoother and can be re?planned when encountering new obstacles due to various reasons. It can be concluded with experimental results that the proposed method can plan the optimal route for both static and dynamic maps quickly and accurately， and its application in various environments can obtain path planning results efficiently.

Keywords： multi?obstacle; inspection robot; path planning; D* algorithm; dynamic environment; extended node; cost function; extended step size

0" 引" 言

傳統人工巡檢方式不但時間效率低下，而且容易產生疏漏，在這種情況下使用巡檢機器人代替人工進行巡檢是一種十分高效并且節省成本的做法。巡檢機器人可以被放置在地形復雜[1]、危險性較高的環境中進行巡檢，能夠有效防止巡檢人員受傷。但是在復雜多障礙環境下巡檢機器人的路徑規劃是一個十分困難的問題[2]。路徑規劃直接影響到巡檢效果，若路徑規劃效果差，輕則導致巡檢效果不理想或者巡檢機器人被困，重則出現安全事故引發生命財產損失[3]。……