Trajectory-Based SLAM for Indoor Mobile Robots with Limited Sensing Capabilities

In this paper we introduce a novel SLAM system for 2-D indoor environments that relies only on limited sensing. Our fully autonomous system uses only the trajectory of the robot around walls and objects in the environment as landmarks and is capable of robust and long-term exploration and mapping of a broad range of household floor plans. Rank-deficient and full-rank factors are created when the robot observes existing trajectory-based landmarks, and they are filtered and added in a pose graph, which is optimized periodically. The mission space is mapped by efficient adaptive local mapping algorithms. The proposed SLAM system has been extensively tested in various scenarios, and experimental results show its robustness and accuracy.