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.

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 and Navigation for a Mobile Robot Equipped with Rotating Ultrasonic Sensors Using a Smartphone as the Robot's Brain

2016 ◽  
Vol 7 (1) ◽  
pp. 1-11 ◽  
Author(s):  
Jongil Lim ◽  
Seokju Lee ◽  
Girma Tewolde ◽  
Jaerock Kwon
Keyword(s):  
Mobile Robot ◽  
Indoor Environment ◽  
Indoor Localization ◽  
Robot Navigation ◽  
Heavy Duty ◽  
Current Position ◽  
Distance Measurements ◽  
Current Location ◽  
Computationally Expensive ◽  
Particle Filter Algorithm

Identifying the current location of a robot is a prerequisite for robot navigation. To localize a robot, one popular way is to use particle filters that estimate the posterior probabilistic density of a robot's state space. But this Bayesian recursion approach is computationally expensive. Most microcontrollers in a small mobile robot cannot afford it. The authors propose to use a smartphone as a robot's brain in which heavy-duty computations take place whereas an embedded microcontroller on the robot processes rudimentary sensors such as ultrasonic and touch sensors. In their design, a smartphone is wirelessly connected to a robot via Bluetooth by which distance measurements from the robot are sent to the smartphone. Then the smartphone takes responsible for computationally expensive operations like executing the particle filter algorithm. In this paper, the authors designed a mobile robot and its control architecture to demonstrate that the robot can navigate indoor environment while avoiding obstacles and localize its current position.

scholarly journals An Indoor Localization System Using Residual Learning with Channel State Information

Entropy ◽  
2021 ◽  
Vol 23 (5) ◽  
pp. 574
Author(s):  
Chendong Xu ◽  
Weigang Wang ◽  
Yunwei Zhang ◽  
Jie Qin ◽  
Shujuan Yu ◽  
...  
Keyword(s):  
Channel State Information ◽  
Indoor Environment ◽  
Indoor Localization ◽  
Location Based Services ◽  
Channel State ◽  
State Information ◽  
Localization Accuracy ◽  
Localization System ◽  
Increasing Demand ◽  
Degradation Problem

With the increasing demand of location-based services, neural network (NN)-based intelligent indoor localization has attracted great interest due to its high localization accuracy. However, deep NNs are usually affected by degradation and gradient vanishing. To fill this gap, we propose a novel indoor localization system, including denoising NN and residual network (ResNet), to predict the location of moving object by the channel state information (CSI). In the ResNet, to prevent overfitting, we replace all the residual blocks by the stochastic residual blocks. Specially, we explore the long-range stochastic shortcut connection (LRSSC) to solve the degradation problem and gradient vanishing. To obtain a large receptive field without losing information, we leverage the dilated convolution at the rear of the ResNet. Experimental results are presented to confirm that our system outperforms state-of-the-art methods in a representative indoor environment.

HOLONOMIC AND OMNIDIRECTIONAL LOCOMOTION SYSTEMS FOR WHEELED MOBILE ROBOTS: A REVIEW

2015 ◽  
Vol 77 (28) ◽  
Author(s):  
M. Juhairi Aziz Safar
Keyword(s):  
Mobile Robot ◽  
Mobile Robots ◽  
Degrees Of Freedom ◽  
Wheeled Mobile Robot ◽  
Arbitrary Direction ◽  
Current Position ◽  
Wheeled Mobile Robots ◽  
Future Improvement ◽  
Position And Orientation ◽  
Three Degrees Of Freedom

Holonomic and omnidirectional locomotion systems are best known for their capability to maneuver at any arbitrary direction regardless of their current position and orientation with a three degrees of freedom mobility. This paper summarizes the advancement of holonomic and omnidirectional locomotion systems for wheeled mobile robot applications and discuss the issues and challenges for future improvement.

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.

Experimental investigation for better relative localization of a mobile robot using Taguchi method

Robotica ◽  
2014 ◽  
Vol 33 (7) ◽  
pp. 1415-1423
Author(s):  
T. Mathavaraj Ravikumar ◽  
R. Saravanan
Keyword(s):  
Mathematical Model ◽  
Taguchi Method ◽  
Mobile Robot ◽  
Mobile Robotics ◽  
Kinematic Parameters ◽  
Absolute Position ◽  
Relative Localization ◽  
Wheeled Robot ◽  
Position And Orientation

SUMMARYThe positioning of a wheeled robot is an imperative manipulation problem in mobile robotics. Odometry is a familiar method for determining the relative position of a mobile robot. It comprises the detection of a set of kinematic parameters that permit reconstructing the robot's absolute position and orientation starting from the wheels' encoder measurements. This paper deals with the determination of better relative localization of a mobile robot by means of odometry by considering the influence of parameters namely total weight, speed, diameter of wheel, and width of wheel. Experiments have been conducted based on L9 orthogonal array suggested in Taguchi method to obtain the optimum condition. A mathematical model has also been developed for the mobile robot with the help of MINITAB software.

Localization using infrared beacons

Robotica ◽  
2000 ◽  
Vol 18 (2) ◽  
pp. 153-161 ◽  
Author(s):  
Eric Brassart ◽  
Claude Pegard ◽  
Mustapha Mouaddib
Keyword(s):  
Mobile Robot ◽  
Mobile Robots ◽  
Processing Time ◽  
Ccd Camera ◽  
Localization System ◽  
Triangulation Method ◽  
Time Calibration ◽  
Improve Accuracy ◽  
Position And Orientation

In this paper, we deal with a localization system allowing one to determine the position and orientation of a mobile robot. This system uses active beacons distributed at the ceiling of the navigation area. These beacons can transmit a coded infrared signal which allows the robots to identify the sender. A CCD camera associated to an infrared receiver allows one to compute the position with a triangulation method which needs reduced processing time. Calibration and correcting distortion stages are performed to improve accuracy in the determination of the position. Dynamic localisation is established for most actual mobile robots used in indoor areas.

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