为提高规划主体在复杂环境中运动的通过可行性和安全可靠性，解决路网环境通常不连续和主体大小普遍未计算的问题，基于连续路网环境提出了一种实体化主体路径规划算法。首先根据环境信息和主体大小，采用融合膨胀的策略构建实体化主体连续环境模型(model continuous environment with subject objective，MCESO)，然后采取路网优先(road network priority，RNP)策略，在实体化主体连续环境下利用骨架提取技术得到路网信息，最后以经典A*算法为例，将上述模型融合改进，提出一种路径规划MCESO-RNP-A*算法。仿真实验结果表明，建模方案和规划算法能够使得实体化主体在连续路网环境下安全顺利到达规划指定目标点，并且在大范围环境下相较MCE-A*算法生成路径的时间可降低约30％，验证了算法的可行性和有效性。
Subject objective path planning algorithm based on continuous road network environment
In order to improve the passage feasibility and safety reliability of the movement of the planning subject in a complex environment,and solve the problems of the usually discontinuous road network environment and the general uncalculated size of the subject,a subject objective path planning algorithm based on the continuous road network environment is proposed.Firstly,according to the environment information and subject size,the fusion expansion strategy is used to construct the model continuous environment(MCE)with subject objective(MCESO).Then,the road network priority(RNP)strategy is adopted,and the skeleton extraction technology is used to obtain the road network information in the continuous environment of the subject objective.Finally,the classical A*algorithm is taken as an example,the above model is fused and improved,and a path planning MCESO-RNP-A*algorithm is proposed.Simulation results show that the modeling scheme and planning algorithm can enable the subject objective to reach the target point specified in the planning smoothly in the continuous road network environment,and the time to generate the path can be reduced by about 30％compared with the MCE-A*algorithm in a large range environment,which verifies the feasibility and effectiveness of the algorithm.
万方数据
维普
