摘要：A Kalman filter based algorithm is proposed to improve the loop closure correction performance of Gmapping using low cost and resolution laser scanners (e.g. RPLidar laser scanner), which can positively promote the application of laser scanner in normal life. Maps built up by using different cost and resolution laser scanners are compared with the conclusion that the loop closure performance of Gmapping using RPLidar is relatively bad. To solve the problem, a Kalman filter based correction algorithm is proposed to correct state estimations of Gmapping. Experiments on a TurtleBot using both RPLidar and SICK LMS laser scanners demonstrate the effectiveness of the proposed algorithm.
