2P2-C08 Localization System Based on Magnetic Map for Indoor Mobile Robot

2008 ◽  
Vol 2008 (0) ◽  
pp. _2P2-C08_1-_2P2-C08_2
Author(s):  
Samann Rahok ◽  
Koichi OZAKI
Keyword(s):  
Mobile Robot ◽  
Localization System ◽  
Indoor Mobile Robot

scholarly journals Localization System for Indoor Mobile Robot Using Large Square-Shaped Reflective Marker

2021 ◽  
Vol 15 (2) ◽  
pp. 182-190
Author(s):  
Hiroaki Seki ◽  
Ken Kawai ◽  
Masatoshi Hikizu ◽  
◽  
◽  
...  
Keyword(s):  
Mobile Robot ◽  
Mobile Robot Navigation ◽  
Prototype System ◽  
Localization System ◽  
Indoor Mobile Robot ◽  
Four Corners ◽  
Fisheye Camera ◽  
Position And Orientation ◽  
Marker Detection ◽  
Measurable Range

A localization system using reflective markers and a fisheye camera with blinking infrared lights is useful and safe for mobile robot navigation in an environment with coexisting humans and robots; however, it has the problems of low robustness and a small measurable range for marker detection. A large, square-shaped reflective marker, with solid and dotted edges, is proposed for more reliable localization of indoor mobile robots. It can be easily detected using Hough transform and is robust for occlusion. The coordinates of the four corners of the square-shaped marker determine the robot’s localization. Infrared lighting with a new LED arrangement is designed for a wide measurable range via brightness simulation, including the effect of observation and reflection angles. A prototype system was developed, enabling the 2D position and orientation to be detected with an accuracy of 60 mm and 3◦, respectively, within a 4 m2 area.

Auto-localization system for indoor mobile robot using RFID fusion

Robotica ◽  
2014 ◽  
Vol 33 (9) ◽  
pp. 1899-1908 ◽  
Author(s):  
A. Abdelgawad
Keyword(s):  
Mobile Robot ◽  
Radio Frequency Identification ◽  
Accurate Estimation ◽  
Localization System ◽  
Accurate Localization ◽  
Indoor Mobile Robot ◽  
Current Location ◽  
Frequency Identification ◽  
Passive Rfid ◽  
Estimated Error

SUMMARYAutonomous mobile robots need accurate localization techniques to perform assigned task. Radio Frequency Identification Technology (RFID) has become one of the main means to construct a real-time localization system. Localization techniques in RFID rely on accurate estimation of the read range between the reader and the tags. This paper proposes an auto-localization system for indoor mobile robot using passive RFID. The proposed system reads any three different RFID tags which have a known location. The current location can be estimated using the Time Difference of Arrival (TDOA) scheme. In order to improve the system accuracy, the proposed system fuses the TDOA scheme for the three tags. A Kalman filter is used to minimize the estimated error and predict the next location. The simulation results validate the proposed framework.

Developing a Self-Localization System for Mobile Robot Using Ultrasonic Sensor Mesh

2016 ◽  
Vol 852 ◽  
pp. 812-818
Author(s):  
Rajneesh Deka ◽  
G. Kalaiarasan ◽  
R. Jegadeeshwaran
Keyword(s):  
Mobile Robot ◽  
Ultrasonic Sensor ◽  
Error Threshold ◽  
Localization System ◽  
Best Value ◽  
Indoor Mobile Robot ◽  
Simple Error ◽  
Position And Orientation

A hybrid self-localization system for indoor mobile robot is proposed which is used to get the pose (position and orientation) of the mobile robot within the ultrasonic mesh area while avoiding the drift caused by the odometry system of the robot. This localization system consist of three subsystem-odometry, IMU and ultrasonic mesh. The IMU system is fitted within the robot chassis. The ultrasonic mesh is made by fixing various ultrasonic trans-receivers along two lines parallel to the x-axis at known locations. The IMU system is used to get the heading of the robot and the ultrasonic mesh is used to get the position of the robot, however the odometry system gives both position and orientation of the robot. A simple error threshold based algorithm is used to select the best value of robot pose from the sub-systems.

Synchronous Issue of IR-Based Large Scale Volume Localization System

2014 ◽  
Vol 496-500 ◽  
pp. 1643-1647
Author(s):  
Ying Feng Wu ◽  
Gang Yan Li
Keyword(s):  
Standard Deviation ◽  
Mobile Robot ◽  
Large Volume ◽  
Large Scale ◽  
Image Acquisition ◽  
Mean Value ◽  
Network Synchronization ◽  
Localization System ◽  
Localization Performance ◽  
The Mean

IR-based large scale volume localization system (LSVLS) can localize the mobile robot working in large volume, which is constituted referring to the MSCMS-II. Hundreds cameras in LSVLS must be connected to the control station (PC) through network. Synchronization of cameras which are mounted on different control stations is significant, because the image acquisition of the target must be synchronous to ensure that the target is localized precisely. Software synchronization method is adopted to ensure the synchronization of camera. The mean value of standard deviation of eight cameras mounted on two workstations is 12.53ms, the localization performance of LSVLS is enhanced.

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