Robot Autonomous Exploration and Map Building Method

Abstract

How to enable effective autonomous exploration and construction maps in unknown indoor environments is one of the key issues in the field of mobile robots. The mobile robot autonomous exploration and map building system studied in this paper aims to further improve the autonomy of the indoor mobile robot, so that the robot can independently complete the exploration and map building task in the unknown indoor environment and realize the autonomous navigation and other functions according to the constructed environment map. An independent exploration and SLAM construction method based on the fast exploration random tree (RRT) is proposed, applying the RRT algorithm to the boundary exploration field. Through performing collision tests by randomly spreading the sampling points in the environment and adding the parameters of the adaptive step size, the boundary points are optimized and evaluated for the best explored boundary points. At the same time, using the combination of global RRT and local RRT construction method, it accelerates the exploration of the unknown environment, until throughout the whole environment. Experimental testing in a simulation environment, the experimental results show that the system works very well, and can independently go through the whole environment and complete the map drawing.