• Journal of Institute of Control, Robotics and Systems
• /
• v.19 no.4
• /
• pp.379-384
• /
• 2013

We propose a new global positioning method for the indoor mobile robots. The multiple indoor lights fixed in ceiling are used as the landmarks of positioning system. The ceiling images are acquired by the fisheye lens camera mounted on the moving robot. The position and orientation of the lights are extracted by binarization and labeling techniques. Also the boundary lines between ceiling and walls are extracted to identify the order of each light. The robot position is then calculated from the extracted position and known position of the lights. The proposed system can increase the accuracy and reduce the computation time comparing with the other positioning methods using natural landmark. Experimental results are presented to show the performance of the method.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.39C no.9
• /
• pp.820-827
• /
• 2014

One of the basic problems in Wireless Sensor Networks (WSNs) is the localization of the sensor nodes based on the known location of numerous anchor nodes. WSNs generally consist of a large number of sensor nodes and recording the location of each sensor nodes becomes a difficult task. On the other hand, based on the application environment, the nodes may be subject to mobility and their location changes with time. Therefore, a scheme that will autonomously estimate or calculate the position of the sensor nodes is desirable. This paper presents an intelligent localization scheme, which is an artificial neural network (ANN) based localization scheme used to estimate the position of the unknown nodes. In the proposed method, three anchors nodes are used. The mobile or deployed sensor nodes request a beacon from the anchor nodes and utilizes the received signal strength indicator (RSSI) of the beacons received. The RSSI values vary depending on the distance between the mobile and the anchor nodes. The three RSSI values are used as the input to the ANN in order to estimate the location of the sensor nodes. A feed-forward artificial neural network with back propagation method for training has been employed. An average Euclidian distance error of 0.70 m has been achieved using a ANN having 3 inputs, two hidden layers, and two outputs (x and y coordinates of the position).

• Journal of the Institute of Electronics and Information Engineers
• /
• v.51 no.2
• /
• pp.141-147
• /
• 2014

This paper proposes a robust localization algorithm and optimal number of receivers considering the detection range of underwater targets. The accuracies of the source position, receiver position and sound velocity are improved using the known positions of underwater objects. The accuracies of these parameters influences the performance of the target localization error. Although the source and receiver positions are obtained by the global positioning system (GPS), there are still positional errors due to GPS and variations in sea temperature. First, the influence of those errors are analyzed mathematically and an algorithm is improved to improve the accuracies of source position, receiver position and sound velocity by using geographic points. The performance of the proposed scheme is evaluated in comparison with the conventional algorithm by computer simulations.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.63 no.1
• /
• pp.99-107
• /
• 2014

In this paper, a landmark based localization system using a Kinect sensor is proposed and evaluated with the implemented system for precise and autonomous navigation of low cost robots. The proposed localization method finds the positions of landmark on the image plane and the depth value using color and depth images. The coordinates transforms are defined using the depth value. Using coordinate transformation, the position in the image plane is transformed to the position in the body frame. The ranges between the landmarks and the Kinect sensor are the norm of the landmark positions in body frame. The Kinect sensor position is computed using the tri-lateral whose inputs are the ranges and the known landmark positions. In addition, a new matching method using the pin hole model is proposed to reduce the mismatch between depth and color images. Furthermore, a height error compensation method using the relationship between the body frame and real world coordinates is proposed to reduce the effect of wrong leveling. The error analysis are also given to find out the effect of focal length, principal point and depth value to the range. The experiments using 2D bar code with the implemented system show that the position with less than 3cm error is obtained in enclosed space($3,500mm{\times}3,000mm{\times}2,500mm$).

• Journal of the Korea Institute of Military Science and Technology
• /
• v.16 no.2
• /
• pp.95-100
• /
• 2013

Localization is very important for the autonomous navigation of Unmanned Ground Vehicles; however, it is difficult that they have a precise Inertial Navigation System(INS) sensor, especially Small Unmanned Ground Vehicle(SUGV). Moreover, there are some condition such as denial of global position system(GPS), GPS/INS integrated system is not robust. This paper proposes the estimation algorithm with optical flow sensor and INS. Being compared with previous researches, the proposed algorithm is suitable for skid steering vehicles. We revised the measurement model of previous research for the accuracy of side direction position. Experimental results were performed to verify the algorithm, and the result showed an excellent performance.

• Journal of Institute of Control, Robotics and Systems
• /
• v.21 no.12
• /
• pp.1185-1192
• /
• 2015

In this paper, a study of advanced sound source localization is conducted by eliminating the noise of the sound source using the discrete wavelet transform. And experiments are conducted to evaluate the performance of the proposed system that the mobile robot follows sound source stably. In addition, we compare the position estimation performance by applying a discrete wavelet transform to improve the reliability of the sound signal. The experimental results reveal that the de-nosing filter which removes the noise component in sound source can make the performance of position estimation more precisely and help the mobile robot distinguish the objective sound source clearly.

• Journal of Institute of Control, Robotics and Systems
• /
• v.13 no.10
• /
• pp.956-961
• /
• 2007

We propose a new distance measurement method and local positioning system for the autonomous mobile robots localization. The distance measurement method is able to measure long-range distances with a high accuracy by using ultrasonic sensors. The time of flight of the ultrasonic waves include various noises is calculated accurately by the proposed period detecting method. The proposed local positioning system is composed of four ultrasonic transmitters and one ultrasonic receiver. The ultrasonic transmitter and receiver are separated but they are synchronized by RF (Radio frequency) signal. The proposed system using ultrasonic waves is represented as USAT(Ultrasonic Satellite System). USAT is able to estimate the position using the least square estimation. The experimental results show that the proposed local positioning system enables to estimate the absolute position precisely.

• Journal of Institute of Control, Robotics and Systems
• /
• v.17 no.2
• /
• pp.108-115
• /
• 2011

This paper describes a new sensor system for mobile robot motion estimation using stereo infrared light sources and a camera. Visibility is being applied to robotic obstacle avoidance path planning and localization. Using simple visibility computation, the environment is partitioned into many visibility sectors. Based on the recognized edges, the sector a robot belongs to is identified and this greatly reduces the search area for localization. Geometric modeling of the vision system enables the estimation of the characteristic pixel position with respect to the robot movement. Finite difference analysis is used for incremental movement and the error sources are investigated. With two characteristic points in the image such as vertices, the robot position and orientation are successfully estimated.

• Journal of Institute of Control, Robotics and Systems
• /
• v.14 no.8
• /
• pp.767-773
• /
• 2008

This paper presents a localization system based on the use of electric compass and tracking IR light source. Digital RGB(Red, Green, Blue)signal of digital CMOS Camera is sent to CPLD which converts the color image to binary image at 30 frames per second. CMOS camera has IR filter and UV filter in front of CMOS cell. The filters cut off above 720nm light source. Binary output data of CPLD is sent to DSP that rapidly tracks the IR light source by moving Camera tilt DC motor. At a robot toward north, electric compass signals and IR light source angles which are used for calculating the data of the location system. Because geomagnetic field is linear in local position, this location system is possible. Finally, it is shown that position error is within ${\pm}1.3cm$ in this system.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.13 no.2
• /
• pp.133-139
• /
• 2013

This paper proposes a vision-based indoor localization method for autonomous vehicles. A single upward-facing digital camera was mounted on an autonomous vehicle and used as a vision sensor to identify artificial landmarks and any natural corner features. An interest point detector was used to find the natural features. Using an optical flow detection algorithm, information related to the direction and vehicle translation was defined. This information was used to track the vehicle movements. Random noise related to uneven light disrupted the calculation of the vehicle translation. Thus, to estimate the vehicle translation, a Kalman filter was used to calculate the vehicle position. These algorithms were tested on a vehicle in a real environment. The image processing method could recognize the landmarks precisely, while the Kalman filter algorithm could estimate the vehicle's position accurately. The experimental results confirmed that the proposed approaches can be implemented in practical situations.