Research on navigation and mapping in pregnancy pig house based on laser-vision fusion technology
Research has been conducted to address the problem of insufficient accuracy of the laser-based or vision-based navigation technologies in the complex facility environment of large-scale pig farms.In the present study,a new method was established by calibrating the intrinsic parameters of depth cameras,fusing data from laser radar and depth cameras for front-end odometry,and comprehensive optimization for back-end processing,loop closure detec-tion,and mapping.A comparative study was conducted to evaluate the effectiveness of constructing 2D grid maps and point cloud maps by using laser-vision fusion mapping technology for passages and corridors.The results demonstra-ted that the fused 2D grid map provided more information than the single laser radar mapping,and it also displayed an intuitive point cloud representation,which could effectively present the road and color information from the actual scene .The relative error ranges for the coornidates of the starting potint and the terminal point were 0.02％-0.33％ and 0.48％-1.62％,respectively,which were lower than those of the three algorithms used for laser mapping,in-dicating good accuracy and mapping efficiency.
lidardepth camerasimultaneous localization and mappingfusion navigation mappingpig house
万方数据
维普
