改进A^(*)和DWA融合的移动机器人导航算法

Mobile Robot Navigation Method Based on Fusion of Improved A^(*)Algorithm and Dynamic Window Approach

针对在移动机器人导航过程中,单一使用A^(*)算法或DWA(Dynamic Window Approach)算法无法兼具全局路径最优与实时避障的问题,提出一种基于改进A^(*)与DWA相融合的移动机器人导航算法.首先,在改进A^(*)算法中,引入环境信息自适应调整代价函数,提高搜索效率;并利用一种关键点选取策略剔除冗余点,保留必要的路径节点,从而规划出只具有关键点的全局路径.然后,在全局路径的基础上,构造结合关键点信息的DWA算法评价函数,进而应用DWA算法以关键点作为中间目标点规划局部路径,提高路径平滑性,实现全局路径最优以及实时避障功能.最后,通过仿真实验和真实环境实验的联合论证,验证了所提出导航算法的有效性和可行性.

In mobile robot navigation,aiming at the problem that only using A^(*)algorithm or dynamic window approach cannot combine global path optimization and real-time obstacle avoidance.A mobile robot navigation algorithm based on the fusion of improved A^(*)algorithm and dynamic window approach is proposed.First,in the improved A^(*)algorithm,the cost function is adaptively adjusted to improve the search efficiency of A^(*)algorithm by introducing environmental information.A key node selection strategy is utilized to eliminate the redundant nodes and retain necessary path nodes,thereby planning a global path with only key nodes.Then,on the basis of the global path,the evaluation function of dynamic window approach combined with key nodes information is constructed.The dynamic window approach is applied to plan the local path with the key nodes as the intermediate target points to improve the smoothness of the path,so as to achieve the global path optimization and real-time obstacle avoidance function.Finally,through the joint demonstration of simulation experiment and real environment experiment,the validity and feasibility of the proposed navigation algorithm are verified.