Research On SLAM Of Mobile Robot Based On Multi Source Information Fusion In Sensor Network Environment

With the development of artificial intelligence and sensor technology,Simultaneous Localization and Mapping(SLAM)technology of mobile robots is attracting much attention.However,the existing SLAM technology of mobile robot has the problems of inaccurate positioning and low efficiency of mapping,which can no longer meet the needs of indoor complex environment.Therefore,it is necessary to combine Wireless sensor networks(WSNs)with mobile robot to form a hybrid system of wireless sensor networks and mobile robot.The system not only reduces the cumulative error of mobile robot positioning by using wireless sensor network,but also makes real-time decision planning by using mobile robot.Under the background of combining wireless sensor network with mobile robot,this paper is devoted to the research of SLAM algorithm of mobile robot based on multi-source information fusion in sensor network environment.The main research contents are as follows:(1)Aiming at the problem of cumulative error caused by long-term movement of mobile robots by traditional SLAM algorithm,a wireless sensor networks assisted SLAM algorithm for mobile robots is proposed in this paper.Firstly,the algorithm introduces a wireless sensor networks based on Ultra Wide Band(UWB)technology,namely UWB sensor networks.When the location of UWB sensor network nodes are known,The Unscented Kalman Filter(UKF)algorithm fuses the IMU and UWB sensor network information to realize the local pose estimation of mobile robots,and provides a good initial value for the scanning matching algorithm.Then the global optimization algorithm is used to obtain the globally consistent map and the global optimal pose of the mobile robot.Finally,the simulation results show that the proposed algorithm has better mapping effect and positioning accuracy than the traditional laser SLAM algorithm.(2)Considering that the location information of UWB sensor network nodes are obtained by manual calibration or carrying GPS,it cannot be efficiently deployed in emergency scenarios and has certain limitations.The SLAM algorithm of wireless sensor networks and mobile robots is further proposed.When the location of the UWB sensor network nodes are unknown,the Unscented Kalman filter algorithm is used to fully integrate various sensor information,and the UWB sensor network nodes and the mobile robot can be located quickly at the same time.At the same time,to solve the problem that there are errors in the measurement values of UWB,which may lead to large errors in the estimated position of the nodes,the global SLAM algorithm is improved,the constraint of UWB sensor network ranging is introduced,the objective function is established,and the optimal estimation of the pose of the mobile robot and the node position of UWB sensor network is achieved by nonlinear optimization method.Finally,the effectiveness of the proposed algorithm is verified by simulation experiments.(3)Building software and hardware experiment platform of mobile robot and wireless sensor networks based on UWB.The interaction between UWB sensor networks and mobile Robot is realized through Robot Operating System(ROS).Finally,the SLAM experiment of wireless sensor networks-assisted mobile robot and SLAM experiment of wireless sensor networks-mobile robot collaboration are carried out indoors through the built hardware and software platform.By comparing with Cartographer algorithm,the feasibility and effectiveness of the proposed algorithm in the actual scenario are verified.