Self-Localization of an Autonomous Mobile Robot Using Fuzzy Adaptive Extended Information Filtering Schemes

• Main Authors: Jui-Cheng Hsu, 徐瑞成
• Other Authors: Ching-Chih Tsai
• Format: Others
• Language: en_US
• Published: 2002
• Online Access: http://ndltd.ncl.edu.tw/handle/91418238242813128326

碩士 === 國立中興大學 === 電機工程學系 === 90 === This thesis develops methodologies and techniques for self-localization of an autonomous mobile robot (AMR) using the fuzzy adaptive extended information filtering (FAEIF) scheme. The FAEIF, composed of a fuzzy tuner and the exponential weighted extended information filter (EIF), is presented in order to detect and avoid the nonlinear filter divergence problems. The main features of the FAEIF scheme are studied in some details. Two novel localization systems together with the FAEIF signal processing methods are proposed to improve the accuracy and robustness of pose estimation for the AMR. The first one based on the three-point triangulation uses a laser scanner and at least three retro-reflectors. The second one fuses ultrasonic time-of-flight (TOF) readings measured from two ultrasonic transmitters and three receivers. In these two methods, not only the static position and orientation of the AMR can be determined uniquely with respect to an inertial frame of reference, but also the dynamic pose estimates can be obtained by the FAEIF-based sensor fusion approach. Numerous simulation and experimental results are provided to show the effectiveness and feasibility of the proposed localization systems and the FAEIF signal processing methods.