Research On Path Planning Methods For Indoor Navigation

As an indispensable foundation of a large amount of emerging technologies,location-based services have played a pivotal role in the national economy and people's daily life.At present,as outdoor localization technology is becoming more and more mature,it is widely used in the fields of localization,navigation,synchronous timing,etc.Meanwhile,the research on indoor localization is also gradually deepened,playing an important role in aspects of smart warehouse,special population monitoring,emergency safety rescue,tourist attraction guidance,etc.With the rapid development of 5G technology,the demands for location value-added services,such as indoor navigation based on 5G,are constantly increasing in scenarios such as target pathfinding and crowd grooming in large crowded indoor places.While indoor path planning technology is one of the core technologies of indoor navigation,existing methods are yet to effectively meet the practical and time-effective requirements of indoor navigation.Thus,a path planning method for indoor navigation is proposed in this paper,which aims to satisfy the demands of indoor location-based services in people's daily lives.The main work of the paper is as follows:Firstly,the paper proposes a single-floor path planning method to solve the problems of low path search efficiency and poor quality of planned path results.This method uses an improved Rapidly Exploring Random Tree(RRT)algorithm to avoid the modeling of indoor environmental space,which improves the efficiency of path planning mainly by three ways: generating random expansion trees bidirectionally,guiding nodes to grow to the target point and adopting a local cache mechanism,respectively.It guarantees the practicality and security of the planning results by sacrificing part of path lengths,and becomes closer to the optimal solution through path smoothing.Secondly,in order to ensure the efficiency and safety requirements of path planning,the paper proposes a multi-floor path planning method.Based on the method above,path planning between multiple floors can be abstracted as a problem of channel selection between them.When the real-time positions of pedestrians can be obtained,this method used a beetle colony antennae search algorithm to search a proper channel.By designing a reasonable fitness function,the method improves the efficiency of path planning and the ability of jumping out of local optimal solutions,which comprehensively considers factors such as the degree of congestion in the indoor environment,the preferences and interactions between different pedestrians,and adaptive step size group search strategies.The two methods above are organically combined to form a path planning solution for indoor navigation,which meets the basic needs of indoor navigation in people's daily life.Finally,the paper conducts a series of comparative simulation experiments,which verify the effectiveness of the proposed methods in it.In particular,the experiments verify the superiority of the single-floor path planning method in aspects of planned path length and planning time consumption.In addition,the experiments also verify the superiority of the multi-floor path planning method in aspects of convergence speed and planning time consumption.