Autonomous Navigation Of Mobile Robot Based On Monocular Video Path And Laser Radar

The navigation of mobile robot is a research hotspot in the field of robotics.The vision sensor,as a tool closest to the human environment perception,has incomparable advantage when compared with other sensors.In this thesis,the vision navigation of mobile robot is studied.Considering the cost and real-time performance of robot navigation,a navigation method based on monocular video path and 2D laser radar is proposed.The method is based on the dual view localization in monocular vision,to achieve obstacle avoidance in unknown environment.The main work of this thesis includes three aspects: visual location,path planning,and autonomous obstacle avoidance.Part ?,visual location.Based on the dual view localization in monocular vision,this thesis introduces the video sequence of the reference path and extracts the ordered key images.Harris corner algorithm is used to extract image feature points,and zero mean normalized cross correlation algorithm is used to match image.According to the constraints between the current image and the most approximate key image,the basic matrix is obtained and optimized.Then the mobile robot can get their pose parameters,and complete visual positioning.Part ?,path planning.Under the guidance of the video path,the mobile robot can judge the position of the centroid of the points shared by the current image and the key images.Taking the centroid as the reference,the visual path tracking is carried out.The mobile robot can walk along the reference path to realize the path planning.Part ?,autonomous obstacle avoidance.In this thesis,the mobile robot uses laser radar for ranging,and a grid map for completing obstacle avoidance control modeling.By defining a series of parameters,such as obstacle avoidance risk function,collision function,movement speed and movement curvature,the obstacle avoidance process is divided into three stages,which can realize the autonomousobstacle avoidance in the above navigation process.Finally,in the real environment,based on the independent research and development platform,the proposed navigation method is verified,which proves that the method has a good practicability in outdoor environment.