为保证各舰船之间的协同占位或位置协调,确定各舰船需要占据的位置或区域,提出舰船多智能体协同占位方案数学建模优化方法.以舰船多智能体运动数学模型为基础,分析各个舰船智能体的运动和航行状态,判断各个智能体的航行领域,并确定舰船智能体的最近会遇距离;采用MADDPG(Multi-Agent Deep Deterministic Policy Gradient)算法结合该距离构建舰船多智能体多元组,以此获取舰船多智能体最佳的占位决策结果;在此基础上,引入同结构变换优化舰船多智能体占位编队结构,保证每个个体的精准占位以及位姿状态的一致性.测试结果表明,该方法能够有效完成各个智能体的位置决策,保证编队位姿状态的一致性,整个舰船智能体编队位置和理想位置之间的误差均低于(5,5)m.
Mathematical modeling and optimization analysis of multi agent collaborative space allocation scheme for ships
To ensure collaborative occupancy or position coordination among ships,determine the positions or areas that each ship needs to occupy,and propose a mathematical modeling optimization method for ship multi-agent collaborat-ive occupancy scheme.Based on the mathematical model of ship multi-agent motion,analyze the motion and navigation status of each ship intelligent agent,determine the navigation domain of each intelligent agent,and determine the nearest en-counter distance of the ship intelligent agent.Using the MADDPG(Multi Agent Deep Determining Policy gradient)al-gorithm combined with this distance to construct a multi-agent multi group for ships,in order to obtain the optimal occu-pancy decision results for ship multi-agent systems.On this basis,the same structure transformation is introduced to optim-ize the formation structure of ship multi-agent occupancy,ensuring accurate occupancy and consistency of pose state for each individual.The test results show that this method can effectively complete the position decision-making of various intel-ligent agents,ensure the consistency of the formation pose state,and the error between the position of the entire ship intelli-gent agent formation and the ideal position is less than(5,5)m.
multi-intelligent agents for shipscollaborative occupancy planmathematical modeling optimizationpose state
万方数据
维普
