During path planning, it is necessary to satisfy the requirements of multiple objectives. Multi-objective synthesis is based on the need of flight mission and subjectivity inclination of decision-maker. The decision-m...During path planning, it is necessary to satisfy the requirements of multiple objectives. Multi-objective synthesis is based on the need of flight mission and subjectivity inclination of decision-maker. The decision-maker, however, has illegibility for under- standing the requirements of multiple objectives and the subjectivity inclination. It is important to develop a reasonable cost performance index for describing the illegibility of the decision-maker in multi-objective path planning. Based on Voronoi dia- gram method for the path planning, this paper studies the synthesis method of the multi-objective cost performance index. Ac- cording to the application of the cost performance index to the path planning based on Voronoi diagram method, this paper ana- lyzes the cost performance index which has been referred to at present. The analysis shows the insufficiency of the cost per- formance index at present, i.e., it is difficult to synthesize sub-objective flmctions because of the great disparity of the sub-objective fimctions. Thus, a new approach is developed to optimize the cost performance index with the multi-objective fuzzy optimization strategy, and an improved performance index is established, which could coordinate the weight conflict of the sub-objective functions. Finally, the experimental result shows the effectiveness of the proposed approach.展开更多
In recent years,the path planning for multi-agent technology has gradually matured,and has made breakthrough progress.The main difficulties in path planning for multi-agent are large state space,long algorithm running...In recent years,the path planning for multi-agent technology has gradually matured,and has made breakthrough progress.The main difficulties in path planning for multi-agent are large state space,long algorithm running time,multiple optimization objectives,and asynchronous action of multiple agents.To solve the above problems,this paper first introduces the main problem of the research:multi-objective multi-agent path finding with asynchronous action,and proposes the algorithm framework of multi-objective loose synchronous(MO-LS)search.By combining A*and M*,MO-LS-A*and MO-LS-M*algorithms are respectively proposed.The completeness and optimality of the algorithm are proved,and a series of comparative experiments are designed to analyze the factors affecting the performance of the algorithm,verifying that the proposed MO-LS-M*algorithm has certain advantages.展开更多
文摘During path planning, it is necessary to satisfy the requirements of multiple objectives. Multi-objective synthesis is based on the need of flight mission and subjectivity inclination of decision-maker. The decision-maker, however, has illegibility for under- standing the requirements of multiple objectives and the subjectivity inclination. It is important to develop a reasonable cost performance index for describing the illegibility of the decision-maker in multi-objective path planning. Based on Voronoi dia- gram method for the path planning, this paper studies the synthesis method of the multi-objective cost performance index. Ac- cording to the application of the cost performance index to the path planning based on Voronoi diagram method, this paper ana- lyzes the cost performance index which has been referred to at present. The analysis shows the insufficiency of the cost per- formance index at present, i.e., it is difficult to synthesize sub-objective flmctions because of the great disparity of the sub-objective fimctions. Thus, a new approach is developed to optimize the cost performance index with the multi-objective fuzzy optimization strategy, and an improved performance index is established, which could coordinate the weight conflict of the sub-objective functions. Finally, the experimental result shows the effectiveness of the proposed approach.
基金Aeronautical Science Foundation of China(No.20220001057001)。
文摘In recent years,the path planning for multi-agent technology has gradually matured,and has made breakthrough progress.The main difficulties in path planning for multi-agent are large state space,long algorithm running time,multiple optimization objectives,and asynchronous action of multiple agents.To solve the above problems,this paper first introduces the main problem of the research:multi-objective multi-agent path finding with asynchronous action,and proposes the algorithm framework of multi-objective loose synchronous(MO-LS)search.By combining A*and M*,MO-LS-A*and MO-LS-M*algorithms are respectively proposed.The completeness and optimality of the algorithm are proved,and a series of comparative experiments are designed to analyze the factors affecting the performance of the algorithm,verifying that the proposed MO-LS-M*algorithm has certain advantages.