The Intelligent Cleaning Robot Map Building And Create The Association Algorithm

In recent years, with the technological advances and improve the living standards of people, intelligent home appliances such as robot cleaner began to appear in people's lives. Robot cleaner is begun to give more and more attention, and the demands to complete the autonomous tasks become Increasing. But map of unknown environment of the robot is a key link in a series of tasks. This paper mainly on the robot cleaner's environment map building and the research of the data association algorithm of the environment map building. It includes the following aspects:Firstly this paper studied indoor local map building and indoor feature point detection with robot cleaner. Robot cleaner obtained distance data with range sensor, through to the environmental data based on distance segmentation got all linear area, then to the linear area with least-square method for linear fitting, realized the local maps to create, simultaneously according to people awareness of the environment, completing the corner and breakpoint detection.Secondly this paper studied the SLAM algorithm, designed and realized the EKF-SLAM algorithm. This algorithm can improve the robot cleaner localization accuracy and provides conditions for global map creating.Thirdly focusing on analyzing the data association problem in the SLAM algorithm, an algorithm base on indoor environment of sequential compatibility nearest neighbor is presented. This method will give weights to each feature point, according to weight's order, priority chooses feature points with greater associated possibility to associate, improve the associated precision.Finally, a method for creating global map by integration the local map and the global map is presented. This method compares the position of lines in the local map and the global map, and then divides them into related line, new line, temporary line, by different processing flow, at last realizes the global map of creating.