Title :
MATLAB-based simulators for mobile robot Simultaneous Localization and Mapping
Author :
Chen, Chen ; Cheng, Yinhang
Author_Institution :
Sch. of Electron. & Inf. Eng., Beijing Jiaotong Univ., Beijing, China
Abstract :
Mobile robot Simultaneous Localization and Mapping (SLAM) problem is one of the most active research areas in robotics. In the research and simulation of SLAM, MATLAB-based simulators are widely used due to their comprehensive functionalities and simple usage. In this paper, the main open source MATLAB-based simulators for SLAM and their properties are listed. Two representative ones are concretely introduced from the aspects of data creation and import, motion model and observation model, and algorithms implementation. Simulation results of these two simulators indicate that MATLAB-based simulators are convenient and helpful in the robot SLAM research when developing new algorithms and when comparing accuracy, consistency or convergence of different algorithms. The SLAM algorithms widely used in MATLAB-based simulators, including Extended Kalman Filter (EKF), Unscented Kalman Filter (UKF) based SLAM algorithm and FastSLAM algorithm, are also introduced.
Keywords :
Kalman filters; SLAM (robots); digital simulation; mathematics computing; mobile robots; FastSLAM algorithm; MATLAB-based simulator; SLAM algorithm; data creation; extended Kalman filter; mobile robot simultaneous localization and mapping; motion model; observation model; unscented Kalman filter; Computer languages; Gold; MATLAB; Simultaneous localization and mapping; EKF; MATLAB-based simulators; SLAM; mobile robot; motion model; observation model;
Conference_Titel :
Advanced Computer Theory and Engineering (ICACTE), 2010 3rd International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-6539-2
DOI :
10.1109/ICACTE.2010.5579471