SLAM algorithm and Navigation for Indoor Mobile Robot Based on ROS

Abstract

SLAM and path planning are indispensable technologies for studying robot navigation performance. Aiming at the problem of simultaneous localization and mapping, the mapping effects of Gmapping algorithm and Cartographer algorithm are compared in terms of external contour and mapping accuracy. Aiming at the problem of global path planning and obstacle avoidance, Dijkstra algorithm and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathrm{A}^{\ast}$</tex> algorithm are analyzed and compared, and TEB algorithm is combined to realize autonomous navigation. Through the indoor environment testing, The Cartographer algorithm produces clearer and more accurate maps, and Dijkstra algorithm has a slight advantage over <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathrm{A}^{\ast}$</tex> algorithm in terms of path length and smoothness in the environment with U-shaped obstacles. This paper verifies the feasibility and effectiveness of the system from two aspects, which is of great significance to the research of robot in indoor environment.