TY - JOUR A2 - Wörn, Heinz AU - Kuo, Bor-Woei AU - Chang, Hsun-Hao AU - Chen, Yung-Chang AU - Huang, Shi-Yu PY - 2011 DA - 2011/06/08 TI - A Light-and-Fast SLAM Algorithm for Robots in Indoor Environments Using Line Segment Map SP - 257852 VL - 2011 AB - Simultaneous Localization and Mapping (SLAM) is an important technique for robotic system navigation. Due to the high complexity of the algorithm, SLAM usually needs long computational time or large amount of memory to achieve accurate results. In this paper, we present a lightweight Rao-Blackwellized particle filter- (RBPF-) based SLAM algorithm for indoor environments, which uses line segments extracted from the laser range finder as the fundamental map structure so as to reduce the memory usage. Since most major structures of indoor environments are usually orthogonal to each other, we can also efficiently increase the accuracy and reduce the complexity of our algorithm by exploiting this orthogonal property of line segments, that is, we treat line segments that are parallel or perpendicular to each other in a special way when calculating the importance weight of each particle. Experimental results shows that our work is capable of drawing maps in complex indoor environments, needing only very low amount of memory and much less computational time as compared to other grid map-based RBPF SLAM algorithms. SN - 1687-9600 UR - https://doi.org/10.1155/2011/257852 DO - 10.1155/2011/257852 JF - Journal of Robotics PB - Hindawi Publishing Corporation KW - ER -