Simultaneous localization and mapping: A feature-based probabilistic approach
نویسنده
چکیده
This article provides an introduction to Simultaneous Localization And Mapping (SLAM), with the focus on probabilistic SLAM utilizing a feature-based description of the environment. A probabilistic formulation of the SLAM problem is introduced, and a solution based on the Extended Kalman Filter (EKF-SLAM) is shown. Important issues of convergence, consistency, observability, data association and scaling in EKF-SLAM are discussed from both theoretical and practical points of view. Major extensions to the basic EKF-SLAM method and some recent advances in SLAM are also presented.
منابع مشابه
Effects of Moving Landmark’s Speed on Multi-Robot Simultaneous Localization and Mapping in Dynamic Environments
Even when simultaneous localization and mapping (SLAM) solutions have been broadly developed, the vast majority of them relate to a single robot performing measurements in static environments. Researches show that the performance of SLAM algorithms deteriorates under dynamic environments. In this paper, a multi-robot simultaneous localization and mapping (MR-SLAM) system is implemented within a...
متن کاملExperimental Validation of Fastslam Algorithm Characterized by a Linear Features Based Map
In this paper the simultaneous localization and mapping problem in an unknown indoor environment is addressed. A probabilistic approach based on FastSLAM algorithm and line feature map is described. Experimental results performed with a smart wheelchair in an indoor environment are introduced and discussed. Copyright IFAC 2006 c ©
متن کاملMap-merging in Multi-robot Simultaneous Localization and Mapping Process Using Two Heterogeneous Ground Robots
In this article, a fast and reliable map-merging algorithm is proposed to produce a global two dimensional map of an indoor environment in a multi-robot simultaneous localization and mapping (SLAM) process. In SLAM process, to find its way in this environment, a robot should be able to determine its position relative to a map formed from its observations. To solve this complex problem, simultan...
متن کاملExperimental validation of FastSLAM algorithm integrated with a linear features based map
In this paper the Simultaneous Localization And Mapping (SLAM) problem in unknown indoor environments is addressed. A probabilistic approach integrating FastSLAM algorithm and a line feature map is developed and validated. Experimental validation is performed by a smart wheelchair equipped with proprioceptive and exteroceptive sensors in an office like environment where loop closing is achieved...
متن کاملSLAM with SC - PHD Filters
By Chee Sing Lee, Sharad Nagappa, Narcis Palomeras, Daniel E. Clark, and Joaquim Salvi An Underwater Vehicle Application T he random finite-set formulation for multiobject estimation provides a means of estimating the number of objects in cluttered environments with missed detections within a unified probabilistic framework. This methodology is now becoming the dominant mathematical framework w...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Applied Mathematics and Computer Science
دوره 19 شماره
صفحات -
تاریخ انتشار 2009