| In recent years,with the rising labor cost and increasing client demand,intelligent mobile robots have been widely used in intelligent factory,logistics handling,intelligent inspection and other fields.The localization and navigation technology of intelligent mobile robot in indoor and outdoor changing environment is one of the key problems in adapting to the development and application of multiple scenarios.At present,domestic and foreign scholars have done a lot of research on positioning and navigation based on intelligent mobile robots in indoor and outdoor alternating environment.The main method is to realize real-time navigation by carrying indoor and outdoor positioning sensors respectively.However,because the actual indoor and outdoor working scenes are complex and changeable,and the sensor itself has the inevitable accumulation of errors,the reliability and flexibility of indoor and outdoor positioning and navigation need to be improved.Therefore,in view of the existing problems,this paper proposes a positioning and navigation technology based on multi-source sensor fusion positioning model and dynamic confidence based indoor and outdoor local raster map stitching method for relocation.The mobile robot can realize multi-scene map stitching and positioning navigation in indoor and outdoor alternating environment.(1)By analyzing the performance and positioning effect of the current positioning sensors widely applicable to indoor and outdoor,combined with the actual selection of sensors in indoor and outdoor environment,it is determined to use Lidar,GPS,IMU,Odom,and electromagnetic sensors to construct the multi-source sensor fusion model.The model is mainly classified into indoor environment,outdoor narrow environment,outdoor open environment and indoor/outdoor alternating environment.The signal fusion modes of Lidar /IMU/Odom,Lidar /GPS,laser SLAM/ electromagnetic sensor and lidar.(2)The matching between the prior static map and the real-time positioning sensor can effectively improve the positioning and navigation stability and accuracy of intelligent mobile robots.Aiming at the problem that two dimensional raster maps created by SLAM technology in indoor and outdoor environments cannot contain both indoor and outdoor point cloud information,this paper proposes an indoor and outdoor raster map splicing method based on dynamic confidence.Firstly,two virtual robot hosts with master-slave structure were established according to the method of multi-robot collaborative positioning and mapping,and the created two-dimensional local raster map was converted into images and saved as the topics of the two robots.By calling SIFT feature detection algorithm,the method of image feature matching was realized.Aiming at the problems of high similarity of raster map features and fuzzy edge features,a dynamic confidence adjustment method is proposed to improve the success rate of raster map stitching.This paper introduces the stitching process in detail,and tests the stitching effect of raster map in different environments to verify the effectiveness of the dynamic confidence optimization method.(3)The robot operating environment is built in the ROS robot operating system.The indoor and outdoor maps are used as the prior static maps in navigation and the real-time positioning data of the multi-source sensor fusion model are matched to realize relocation.In a unified map coordinate system,the robot positioning and navigation system navigates from the start point to the target point by calling the global and local path planning algorithms,and verifies the reliability of the navigation system based on the multi-source fusion model and a prior static map through the positioning coordinates of the target points.(4)The positioning and navigation experiment of mobile robot is carried out in the actual indoor and outdoor alternating environment.By setting up the experimental environment and experimental platform,the reliability and accuracy of the multi-source sensor model and patchwork map under indoor environment,outdoor environment and indoor and outdoor alternating environment are tested.The experimental results show that the average error of x axis 0.16 m and y axis 0.15 m can be achieved by fusion positioning method.The navigation accuracy of the Mosaic map as a prior static map can reach x axis0.20 m and y axis 0.06 m,and the navigation accuracy based on the multi-source fusion model and prior static map relocation can reach x axis 0.17 m and y axis 0.22 m.This paper preliminarily verifies the stability and reliability of the proposed method in realizing the positioning and navigation of mobile robots in the alternating environment between indoor and outdoor. |
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