Application Research Of Robot Indoor Navigation And Obstacle Avoidance System

In recent years,with the rapid development of robotics,one of the branches of the robotics,the problem of navigation and obstacle avoidance on moving robot is also highly concerned,there is no doubt that it has made great progress.Assuredly,if we intend to promote the Accuracy of navigation and obstacle avoidance,we are supposed to analyze and consider localization algorithms and path planning algorithms,it has important theoretical significance and application value.In this thesis,first of all we have compiled the research status of positioning algorithm and path planning algorithm from scholars at home and abroad.Secondly,we analyze and compare several algorithms of localization,path planning and mapping,then we have determined the system suggestion in this thesis.Afterwards,in order to solve the problem of particle degradation in the resampling stage of the RBPF-SLAM algorithm,we put forward a RBPF-SLAM algorithm based on improved space diffusion resampling algorithm,to a certain extent,the improved algorithm can disperse high weight particles and inhibit particle degradation.It is confirmed by the simulation experiments that the improved algorithm is more stable and accurate than the traditional RBPF-SLAM algorithm.Eventually,amcl package is rewritten,which add the RBPF-SLAM algorithm based on improved space diffusion resampling algorithm code,then indoor navigation and obstacle avoidance system for moving robots based on ladar is achived under the condition of EAI D1 platform,ydlidar X2 L lidar and ROS.