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基于能效準則的改進三維A*智能橋式起重機路徑規劃研究

Enhancing 3D A* path planning of intelligent bridge crane based on energy efficiency criteria

  • 摘要: 智能、綠色、節能、高效已成為起重機等大型物料搬運設備發展的必然趨勢. 針對傳統三維A*算法存在規劃效率低,路徑拐點多,面對目標點被障礙物包圍時路徑復雜度增加等問題,文中提出一種基于能效準則的三維A*路徑規劃算法. 通過優化擴展方向,由26個搜索方向取舍至11個,提高了搜索效率;通過關鍵點選取策略,刪除冗余節點,減少了路徑拐點;通過對評價函數進行改進并引入高度影響因子,降低了路徑復雜度. 仿真結果表明,改進后的三維A*算法搜索效率、拐點數以及評價值明顯優于傳統三維A*算法. 最后,在改進的三維A*算法基礎上,引入時間、路徑長度、路徑拐點數的能效評價指標對多方案進一步優化得出最佳方案,隨著目標位置增高,最優路徑吊裝高度也隨之增高.

     

    Abstract: Intelligent, green, energy-saving, and high-efficiency technologies have become an inevitable trend in the development of large material-handling equipment, such as cranes. To address the problems of traditional three-dimensional (3D) A* algorithm, such as low planning efficiency, numerous path inflection points, and increased path complexity when the target point is surrounded by obstacles, a 3D A* path-planning algorithm based on energy efficiency criteria is proposed in this study. First, by focusing on the problem of expanding many nodes of the traditional 3D A* algorithm and slow operation speed, the proposed algorithm improves the node search strategy, reduces the number of node expansions, and improves the operation speed. Hence, it aims to determine the inaccuracy of the prediction function of the traditional 3D A* algorithm. The traditional 3D A* algorithm heuristic function is improved, and the height influence factor is introduced to solves the path complexity problem when the target point is surrounded by obstacles. This enables its multi-scenario path planning capability. To address the problem of redundant nodes in the traditional 3D A* algorithm, a node deletion strategy is proposed to retain the key nodes and improve the path smoothness. Second, based on the improved 3D A* algorithm, the energy efficiency criterion is introduced to effectively optimize the multi-schemes to arrive at the optimal scheme. Initially, the energy calculation criterion and evaluation criteria of running time and path length are established for the lifting and running mechanisms, respectively, Then, the dimensionalities of exergy, time and path length are processed via the linear normalization method, and the CRITIC weight method is used to assign weights to each index of the evaluation value. Subsequently, by comprehensively considering energy, time, and path length, the final evaluation value is formed to determine the optimal path. Finally, considering the spatial arrangement and operation of the bridge crane in a factory building as an example, environment modeling is conducted on the MATLAB platform, the virtual obstacle is built at the same scale, the operation scheme of the bridge crane lifting the weight at different heights is conducted, and the multi-scheme path planning is conducted before and after the improvement of the algorithm. The results show that compared with the traditional 3D A * algorithm, the improved 3D A* algorithm reduces time by 20.2% and the number of inflection points by 41.7% when lifting height H=0.5 m. Furthermore, when H=1.5 m, time is reduced by 20.9%, and the number of inflection points decrease by 44.4%; when H=2.5 m, time decrease by 23.4% and the number of inflection points decrease by 40%; when H=3.5m, time decreases by 25.8% and the number of inflection points decrease by 33.3%. The optimal operation scheme is selected by introducing the evaluation values of time, energy, and inflection points. The optimal scheme is concluded to be biased toward the lower level with the increase in load, Furthermore, with an increase in the target position height, the height of the optimal solution is expected to increase. In this study, the 3D A* algorithm is improved, and an energy efficiency criterion is introduced. Simulation experiments are conducted, and the results show that the improved 3D A* algorithm based on the energy efficiency criterion is suitable for energy-saving and efficient operation of bridge cranes.

     

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