Research On Bundle Adjustment For Visual SLAM Under Large-Scale Scene

As the scene increases,the time and memory consumed of SLAM optimization will increase greatly.Therefore,real-time operation in the configuration of a low computer or arm platform will be very difficult in the large-scale visual Simultaneous Localization And Mapping(SLAM).At the same time,the map built by SLAM in large-scale scenes is not enough for robot navigation and control.It is important to reduce the time and memory consumption and to establish a better map though bundle adjustment in the large-scale SLAM.And it is very important for the real-time of SLAM system and robot's navigation and path planning.The main contents of this article are as follows:1.Research on Local Bundle Adjustment(LBA)in large-scale scenes.The Local Bundle Adjustment method is analyzed,and an improved LBA is proposed.In creating a new local map,the "five point method" and the distance between the key-frames are used to determine the key-frames that have a closer relationship with the current key-frame to insert into the local map.On the other hand,the application of high-precision map point traction method makes the LBA method to improve the accuracy of optimization.2.Research on Global Bundle Adjustment(GBA)in large-scale scenes.In the Global Bundle Adjustment method,an improved segmentation GBA method is proposed.The number of visible map points between successive key frames is used as the initial segmentation method and then using Ncut(Normalized cut)segmentation method.According to the idea of segmentation,the key-frame sequence to be optimized is divided into a plurality of adjacent sub-sequences,and then only one sub-sequence of motion-position variables needs to be optimized and solved.This method can greatly reduce the optimization variables in the Bundle Adjustment method and ensure the high precision of the system.3.Research on bundle adjustment method of vision and laser fusion SLAM system in large-scale scenes.Analysis of the advantages and disadvantages of a variety of laser SLAM system,select the appropriate laser SLAM system.Laser SLAM has an advantage in creating a navigable map as to visual SLAM,so laser SLAM-assisted methods are used.Using off-line optimization of LBA method,it can get a new and better navigation map.4.Experimental on bundle adjustment based on RGBD visual SLAM System.The improved algorithm is studied and analyzed experimentally,and the experimental results verify the reliability and effectiveness of the algorithm.