Indoor Map Building by Laser Sensor and Positioning Algorithms

2015 ◽  
Vol 764-765 ◽  
pp. 752-756 ◽  
Author(s):  
Jih Gau Juang ◽  
Jia An Wang
Keyword(s):  
Mobile Robot ◽  
Indoor Localization ◽  
Controller Design ◽  
Fuzzy Theory ◽  
Wheeled Mobile Robot ◽  
Laser Sensor ◽  
Map Building ◽  
Map Comparison ◽  
Localization System ◽  
Unknown Environment

This study uses a wheeled mobile robot (WMR) to explore unknown indoor environment and build up a map of the unknown environment. The robot utilizes laser measurement sensor with a indoor localization system to detect obstacles and identify unknown environment. The localization system provides the position of the robot and is used for map comparison. Fuzzy theory is applied to controller design. The proposed control scheme can control the wheeled mobile robot move along walls and avoid obstacles. The Iterative Closest Point (ICP) and the KD-tree are utilized. With sensed data of obstructions and walls, a map of unknown environment can be generated by curve fitting methods.

INDOOR LOCALIZATION OF AN OMNI-DIRECTIONAL WHEELED MOBILE ROBOT

2013 ◽  
Vol 37 (4) ◽  
pp. 1043-1056 ◽  
Author(s):  
Sasha Ginzburg ◽  
Scott Nokleby
Keyword(s):  
Mobile Robot ◽  
Indoor Environment ◽  
Indoor Localization ◽  
Wheeled Mobile Robot ◽  
Fusion Algorithm ◽  
Distance Measurements ◽  
Localization System ◽  
Relative Localization ◽  
Position And Orientation ◽  
Improved Performance

This paper presents a localization system developed for estimating the pose, i.e., position and orientation, of an omni-directional wheeled mobile robot operating in indoor structured environments. The developed system uses a combination of relative and absolute localization methods for pose estimation. Odometry serves as the relative localization method providing pose estimates through the integration of measurements obtained from shaft encoders on the robot’s drive motors. Absolute localization is achieved with a novel GPS-like system that performs localization of active beacons mounted on the mobile robot based on distance measurements to receivers fixed at known positions in the robot’s indoor workspace. A simple data fusion algorithm is used in the localization system to combine the pose estimates from the two localization methods and achieve improved performance. Experimental results demonstrating the performance of the developed system at localizing the omni-directional robot in an indoor environment are presented.

Motion Tracker Based Wheeled Mobile Robot System Identification and Controller Design

2018 ◽  
pp. 241-258
Author(s):  
Dwi Pebrianti ◽  
Yong Hooi Hao ◽  
Nur Aisyah Syafinaz Suarin ◽  
Luhur Bayuaji ◽  
Zulkifli Musa ◽  
...  
Keyword(s):  
System Identification ◽  
Mobile Robot ◽  
Controller Design ◽  
Wheeled Mobile Robot ◽  
Robot System

scholarly journals Backstepping Based Trajectory Tracking Control of a Four Wheeled Mobile Robot

10.5772/6224 ◽  
2008 ◽  
Vol 5 (4) ◽  
pp. 38 ◽  
Author(s):  
Umesh Kumar ◽  
Nagarajan Sukavanam
Keyword(s):  
Mobile Robot ◽  
Trajectory Tracking ◽  
Tracking Control ◽  
Controller Design ◽  
Kinematic Model ◽  
Wheeled Mobile Robot ◽  
Trajectory Tracking Control ◽  
Kinematic Equation ◽  
Pure Rolling ◽  
Tracking Strategy

For a four wheeled mobile robot a trajectory tracking concept is developed based on its kinematics. A trajectory is a time–indexed path in the plane consisting of position and orientation. The mobile robot is modeled as a non holonomic system subject to pure rolling, no slip constraints. To facilitate the controller design the kinematic equation can be converted into chained form using some change of co-ordinates. From the kinematic model of the robot a backstepping based tracking controller is derived. Simulation results demonstrate such trajectory tracking strategy for the kinematics indeed gives rise to an effective methodology to follow the desired trajectory asymptotically.

scholarly journals Noise Reduction for Radio Map Crowdsourcing Building in WLAN Indoor Localization System

2021 ◽  
Author(s):  
liye zhang ◽  
Zhuang Wang ◽  
Xiaoliang Meng ◽  
Chao Fang ◽  
Cong Liu
Keyword(s):  
Indoor Localization ◽  
Sensor Data ◽  
Mode Switching ◽  
Map Building ◽  
Position Information ◽  
Localization Accuracy ◽  
Localization System ◽  
Straight Line ◽  
Indoor Positioning System ◽  
Radio Map

Abstract Recent years have witnessed a growing interest in using WLAN fingerprint-based method for indoor localization system because of its cost effectiveness and availability compared to other localization systems. In order to rapidly deploy WLAN indoor positioning system, the crowdsourcing method is applied to alternate the traditional deployment method. In this paper, we proposed a fast radio map building method utilizing the sensors inside the mobile device and the Multidimensional Scaling (MDS) method. The crowdsourcing method collects RSS and sensor data while the user is walking along a straight line and computes the position information using the sensor data. In order to reduces the noise in the location space of the radio map, the Short Term Fourier Transform (STFT) method is used to detect the usage mode switching to improve the step determination accuracy. When building a radio map, much fewer RSS values are needed using the crowdsourcing method compared to conventional methods, which lends greater influence to noises and erroneous measurements in RSS values. Accordingly, an imprecise radio map is built based on these imprecise RSS values. In order to acquire a smoother radio map and improve the localization accuracy, the MDS method is used to infer an optimal RSS value at each location by exploiting the correlation of RSS values at nearby locations. Experimental results show that the expected goal is achieved by the proposed method.

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