3D Localization and Mapping Using One 2D LIDAR

• Main Authors: Andreas Dopfer, 竇菲
• Other Authors: Chieh-Chih Wang
• Format: Others
• Language: en_US
• Published: 2009
• Online Access: http://ndltd.ncl.edu.tw/handle/74250180586670772937

碩士 === 國立臺灣大學 === 資訊工程學研究所 === 97 === Much work on localization and mapping using LIDAR has been done in mobile robotics. While earlier work was done only in the two dimensional domain, a recent shift towards three dimensional localization and mapping using laser rangefinder can be seen. Three dimensional representations allow a more accurate modeling of the real world, allowing more sophisticated path planning and leading to better obstacle avoidance. Also the performance of localization can be improved,and three dimensional data allows better object recognition than 2D data. Techniques capturing 3D data involve either multiple 2D LIDARS, one 2D LIDAR that is nodded or rotated using an external actuator together with highly accurate orientation sensing and synchronization, or an integrated, expensive 3D scanning system. In this thesis we propose a technique to capture 3D data only using one 2D LIDAR. To do so the robots motion is utilized together with reasonable assumptions. It is assumed that the ground the robot is moving on is flat and visible in the scan, that the sensors height is known and that the environment has vertical structures. First an initial calibration procedure using a camera together with the LIDAR is performed to reveal the extrinsic parameters between robot and the sensor. The localization problem is divided into two steps. The LIDARs sensing plane is tilted away from the robots direction of motion towards the floor (or another known flat structure in the environment). The detection of the floor allows to estimate the angular orientation of the sensor in two dimensions. Using these estimates the range data can be transformed, so that known methods to estimate the missing parameters of the full LIDAR pose can be adopted. Being able to accurately estimate the three dimensional displacement between two consecutive scans allows to build an accurate three dimensional map of the environment.