Path-Planning Research Based On Bayesian Inference And Ant Colony Algorithm For Simulated Aircraft

Virtual reality and simulation technology are applied in virtual simulation training system synthetically, so that weapon equipments'appearance, function, operation and maintenance, and battlefields are simulated realistically. It is an advanced simulation training means that has high information level and good training benefit, and has wide developing space. The problem of simulated aircraft path-planning is an important task in virtual simulation training system. Simulated aircraft environment is a dynamic, uncertain and real-time platform, and in such an adversarial environment, how to realize the real-time aircraft path-planning is a challenge problem.This thesis is based on virtual simulation training system, and the paper mainly researches on path-planning based on Bayesian inference and Ant Colony algorithm for simulated aircraft. Specifically, the major contents of the research presented in this thesis are as follows:Firstly, this paper gives the key technologies of path-planning and its algorithms. Especially, it analyzes the importance of adaptive path-planning and defaults of current research which made an important basis for the research on path- planning in the thesis.Secondly, algorithm of threat level assessment based on Bayesian Network is discussed and its inference model is established. In the threat assessment process, against the threat of diversity and complexity, the paper take into account the threat level of independent threat and superposition threat to improve the accuracy of path-planning algorithm.Grids method and knowledge of graph theory are used to modeling flight space. On this basis, using graph-based ant colony algorithm to solve the global path-planning, at the same time, the results of threat assessment are used into global path-planning and the algorithm is improved according to specific requirements of path-planning. Simulation result shows that the algorithm is effective.Lastly, on the basis of global path-planning, artificial potential field method is used to solve the local path-planning in order to overcome the impact of sudden threats. Simulation result shows that the algorithm is effective.