SLAM-R Algorithm of Simultaneous Localization and Mapping Using RFID for Obstacle Location and Recognition
نویسندگان
چکیده
This paper presents an algorithm of simultaneous localization and mapping (SLAM) with a scanning laser range finder and radiofrequency identification technology (RFID) to include landmarks of an object or place within a generated map. For the testing phase was used of simulation software Anykode’s Marilou and was used to build a virtual mobile robot with the features of the Pionner 3-AT, including a Hokuyo URG-04X scanning laser range finder and an Innovations RFID ID-12 reader. Validation of results was carried out with the cycle closure process to obtain the average error of the navigation path, resulting on an error of less than 50mm.
منابع مشابه
Map-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 کاملEffects 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 کاملNew Adaptive UKF Algorithm to Improve the Accuracy of SLAM
SLAM (Simultaneous Localization and Mapping) is a fundamental problem when an autonomous mobile robot explores an unknown environment by constructing/updating the environment map and localizing itself in this built map. The all-important problem of SLAM is revisited in this paper and a solution based on Adaptive Unscented Kalman Filter (AUKF) is presented. We will explain the detailed algorithm...
متن کاملUsing 3D laser range data for SLAM in outdoor environments
Robot navigation in poorly structured and uneven outdoor environments is an unsolved problem. Thus we present a SLAM (simultaneous localization and mapping) approach that is based on “leveled range scans”. The method is combining 3D perception with 2D localization and mapping. In this way established path planning and 2D navigation algorithms can be used in uneven terrain without the computatio...
متن کاملRobust Simultaneous Localization and Mapping for Very Large Outdoor Environments
This paper addresses the problem of Simultaneous Localization and Mapping (SLAM) when working in very large environments. A Hybrid architecture is presented that makes use of the Extended Kalman Filter to perform SLAM in a very efficient form and a Monte Carlo type filter to resolve the data association problem potentially present when returning to a known location after a large exploration tas...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2014