Research on Navigation and Path Planning of Mobile Robot Based on Vision Sensor

Abstract

The realization of mobile robots' autonomous positioning and map constructing in unknown environments is crucial for the robots' obstacle avoidance and path planning. In this paper, an improved ORB (Oriented fast and Rotated Brief)-SLAM2 (Simultaneous Localization And Mapping 2) algorithm is used to construct a 3D (Three Dimensional) point cloud map of the robot's own positioning and environment. The improved ORB-SLAM2 algorithm is schemed as follows: firstly, after the environment map constructions, it adds the function of saving maps to help implementing map type conversion and navigation obstacle avoidance. Then we employ a PCL (Point Cloud Library) to convert the saved 3D point cloud map into an octomap. A path planning algorithm for mobile robots is implemented on the basis of the octomaps. The robot's dynamical global path planning is implemented using a RRT (Rapidly-exploring Random Tree) algorithm. The experimental results of map constructing and path planning show that the scheme proposed in this paper can effectively realize the obstacle avoidance and path planning of the mobile robot. Thus, the algorithm provides a basis for the further realizing the mobile robot' autonomous movement.