| With the increasing application of artificial intelligence and mobile Internet technology on the mobile terminal,the specialization of equipment in the traditional command system,the single function,and the lack of a good human-machine exchange interface,it is difficult to meet the needs of users in the Internet era.At the same time,in the intelligent command system,how to ensure the real-time,stability,good human-computer interaction,and network adaptability of the command system has become the key technology of the entire system.In response to these problems,this article is based on the research of the traditional command system.The following research has been done:(1)In order to improve the network adaptability of the application,two algorithms of robot source searching and enhanced robot source searching are proposed,and the algorithms are applied to network signal source searching to improve the network adaptability of the application in network instability or other special environments and application scenarios.The first robot source searching algorithm is derived from the beetle antennae search algorithm.Unlike the the beetle antennae search algorithm,this algorithm only requires a "tentacle" and an obstacle avoidance strategy combined with a real scene.The second type of enhanced robot source finding algorithm is to solve the problem that the step size is fixed in the first algorithm,which easily leads to local optimization.The step size is optimized into two types: proportionally decreasing type and dynamically changing type.Global search and local search capabilities.Finally,the algorithm is applied to the search of wireless signal sources in an unknown environment.First,the initial random position and random direction of the mobile robot are used as initial parameters.The motion position of the first step is calculated by the algorithm of this paper.Search for the left and right whiskers in the beetle whisker search algorithm,and combine the obstacle avoidance strategy and the step size update strategy to dynamically change the position of the left and right whiskers and the movement method.Until the completion of the wireless signal source search task.(2)In order to ensure the effectiveness of the proposed algorithm,the algorithm is verified in an experimental simulation environment and real application software.First,a wireless base station search is performed in both indoor and outdoor simulation environments.A large number of simulation experiments show that the algorithm has high search efficiency and can be deployed online.At the same time,it is compared with the classical PSO and GA algorithms.Experimental results show that the algorithm has a small amount of calculations,fast convergence speed,and can always find a position signal source under complex obstacle environments.Secondly,the proposed algorithm is implemented in the command system of Android and IOS.When the connection is disconnected due to the network signal,the network signal source can be implemented by the algorithm until the network is restored.(3)Adopt Ngnix,Redis,Nodejs technology to achieve distributed cluster deployment of cloud servers to ensure the stability,real-time,and scalability of the system.A variety of smart devices,such as Android Phones,Android Tablets,IOS Phones,and IOS Tablets,are used to replace traditional dedicated devices to achieve one device and multiple uses while meeting mainstream device requirements.Designed to achieve user online and offline,location changes,headset control intercom,status display,network signal source search and other features,in addition to meeting the basic intercom functions,provide a good man-machine exchange interface.Finally,through the use of automated testing tools and verification of the stability and reliability of the system in a real environment,it provides a very practical solution for the upgrade of the command system. |
