Map building for a service mobile robot using interactive GUI
ABSTRACT This paper presents a method of map building using interactive GUI for an indoor service mobile robot. The reason we proposed this method is that it is difficult for a mobile robot to generate an accurate map although many kinds of sensors are used. In proposed system, the operator can modify map built by LRF and odometry, compared with the real-time video from web camera using modification tool in developed interactive GUI. In order to improve self-localization of mobile robot, extended Kalman filter (EKF) was used. This paper introduces the architecture of the proposed system and gives some experimental results.
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Article: An introduction to the Kalman filter[show abstract] [hide abstract]
ABSTRACT: In 1960, R.E. Kalman published his famous paper describing a recursive solution to the discrete-data linear filtering problem. Since that time, due in large part to advances in digital computing, the Kalman filter has been the subject of extensive research and application, particularly in the area of autonomous or assisted navigation. The Kalman filter is a set of mathematical equations that provides an efficient computational (recursive) means to estimate the state of a process, in a way that minimizes the mean of the squared error. The filter is very powerful in several aspects: it supports estimations of past, present, and even future states, and it can do so even when the precise nature of the modeled system is unknown. The purpose of this paper is to provide a practical introduction to the discrete Kalman filter. This introduction includes a description and some discussion of the basic discrete Kalman filter, a derivation, description and some discussion of the extended Kalman filter, and a relatively simple (tangible) example with real numbers & results.01/2006;
Conference Proceeding: Mobile robot indoor map building and pose tracking using laser scanningIntelligent Mechatronics and Automation, 2004. Proceedings. 2004 International Conference on; 02/2004
Conference Proceeding: Fuzzy approach for mobile robot positioning[show abstract] [hide abstract]
ABSTRACT: This paper presents a fuzzy approach for positioning an iRobot B21r mobile robot in an indoor environment. A novel error model for the laser rangefinder is built with consideration of the detection distance and the detection angle, and a new concept, the virtual angular point, is introduced as the feature for positioning the mobile robot in this paper. Such points as break points, real angular points, and virtual angular points are employed for positioning a mobile robot. Positions obtained by two arbitrary pairs of feature points are fused together by the weighted mean technique, and the weights are determined by the fuzzy accuracy of the feature points. Experimental study has been carried out to verify the effectiveness of the algorithms.Intelligent Robots and Systems, 2005. (IROS 2005). 2005 IEEE/RSJ International Conference on; 09/2005