scholarly journals MOBILE ROBOT LOCALIZATION USING WLAN SIGNAL STRENGTHS

2014 ◽  
pp. 73-83
Author(s):  
Christof Röhrig ◽  
Frank Künemund
Keyword(s):  
Mobile Robot ◽  
Communication Technology ◽  
Euclidean Distance ◽  
Signal Strength ◽  
Office Building ◽  
Measured Signal ◽  
Robot Localization ◽  
Omnidirectional Antenna ◽  
Mobile Robot Localization ◽  
Radio Map

Many buildings are already equipped with a WLAN infrastructure, as an inexpensive communication technology. In this paper two methods that estimate the position and the heading (pose) of a mobile robot using WLAN technology are described. The proposed techniques for localizing a mobile robot are based on the use of received signal strength values of WLAN access points in range. Both use a radio map based method. For interpolation of the radio map weigthed Euclidean distance and Euclidean distance in combination with Delaunay triangulation is proposed. Measured signal strength values of an omnidirectional antenna and a beam antenna are compared with the values of a radio map, in order to estimate the pose of a mobile robot, whereby the directionality of the beam antenna is used to estimate the heading of the robot. The paper presents the experimental results of measurements in an office building.

scholarly journals MOBILE ROBOT LOCALIZATION USING WLAN, ODOMETRY AND GYROSCOPE DATA

2010 ◽  
pp. 22-30
Author(s):  
Julian Lategahn ◽  
Frank Kuenemund ◽  
Christof Roehrig
Keyword(s):  
Kalman Filter ◽  
Mobile Robot ◽  
Sensor Fusion ◽  
Indoor Environment ◽  
Signal Strength ◽  
Office Building ◽  
Robot Localization ◽  
Mobile Robot Localization ◽  
Radio Map ◽  
Made In

In this paper a method for estimation of position and motion of a mobile robot in an indoor environment is introduced. The proposed method uses WLAN signal strength to estimate the global position of a mobile robot in an office building. Thus signal strengths of the received access points are stored in the radio map in calibration phase. In localization phase the stored values are compared with actually measured one’s. Therefore a fingerprinting algorithm, that was introduced before, is used. The improvement of the presented work is the multi sensor fusion using Kalman filter, which enhances the accuracy of fingerprinting algorithms and tracking of the robot. For this reason odometric and gyroscopic sensors of the robot are fused with the estimated position of the fingerprinting algorithm. The paper presents the experimental results of measurements made in an office building.

3-D Scan Matching for Mobile Robot Localization over Rough Terrain

2019 ◽  
Vol 139 (9) ◽  
pp. 1041-1050
Author(s):  
Hiroyuki Nakagomi ◽  
Yoshihiro Fuse ◽  
Hidehiko Hosaka ◽  
Hironaga Miyamoto ◽  
Takashi Nakamura ◽  
...  
Keyword(s):  
Mobile Robot ◽  
Rough Terrain ◽  
Robot Localization ◽  
Scan Matching ◽  
Mobile Robot Localization

LMI Methods for Extended ℋ∞ Filters for Landmark-based Mobile Robot Localization

2021 ◽  
Author(s):  
Julio Fajardo ◽  
Victor Ferman ◽  
Jabes Guerra ◽  
Antonio Ribas Neto ◽  
Eric Rohmer
Keyword(s):  
Mobile Robot ◽  
Robot Localization ◽  
Mobile Robot Localization

scholarly journals Calibration of ultrasonic sensors of a mobile robot

2009 ◽  
Vol 6 (3) ◽  
pp. 427-437 ◽  
Author(s):  
Ivan Paunovic ◽  
Darko Todorovic ◽  
Miroslav Bozic ◽  
Goran Djordjevic
Keyword(s):  
Signal Processing ◽  
Mobile Robot ◽  
Calibration Procedure ◽  
Ultrasonic Sensor ◽  
Robot Localization ◽  
Ultrasonic Sensors ◽  
Nonlinear Characteristics ◽  
Mobile Robot Localization

The paper discusses a mobile robot localization. Due to cost and simplicity of signal processing, the ultrasonic sensors are very suitable for this application. However, their nonlinear characteristics requires thorough calibrating procedure in order to achieve reliable readings from the obstacles around the robot. Here we describe SMR400 ultrasonic sensor and its calibration procedure. The suggested calibration procedure was tested through a number of experiments, and the results are presented in this paper. .

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