• Journal of Institute of Control, Robotics and Systems
• /
• v.7 no.9
• /
• pp.749-757
• /
• 2001

We present a simple artificial landmark model and robust landmark tracking algorithm for mobile robot localization. The landmark model, consisting of symmetric and repetitive color patches, produces color histograms that are invariant under the geometric and photometric distortions. A stochastic approach based on the CONDENSATION tracks the landmark model robustly even under the varying illumination conditions. After the landmark detection, relative position of the mobile robot to the landmark is calculated. Experimental results show that the proposed landmark model is effective and can be detected and tracked in a clustered scene robustly. With the tracked single landmark, we extract geometrical information than achieve accurate localization.

• 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).

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.18 no.5
• /
• pp.1317-1340
• /
• 2024

With the rapid development of information technology, people's demands on precise indoor positioning are increasing. Wireless sensor network, as the most commonly used indoor positioning sensor, performs a vital part for precise indoor positioning. However, in indoor positioning, obstacles and other uncontrollable factors make the localization precision not very accurate. Ultra-wide band (UWB) can achieve high precision centimeter-level positioning capability. Inertial navigation system (INS), which is a totally independent system of guidance, has high positioning accuracy. The combination of UWB and INS can not only decrease the impact of non-line-of-sight (NLOS) on localization, but also solve the accumulated error problem of inertial navigation system. In the paper, a fused UWB and INS positioning method is presented. The UWB data is firstly clustered using the Fuzzy C-means (FCM). And the Z hypothesis testing is proposed to determine whether there is a NLOS distance on a link where a beacon node is located. If there is, then the beacon node is removed, and conversely used to localize the mobile node using Least Squares localization. When the number of remaining beacon nodes is less than three, a robust extended Kalman filter with M-estimation would be utilized for localizing mobile nodes. The UWB is merged with the INS data by using the extended Kalman filter to acquire the final location estimate. Simulation and experimental results indicate that the proposed method has superior localization precision in comparison with the current algorithms.

• Proceedings of the IEEK Conference
• /
• 2008.06a
• /
• pp.673-674
• /
• 2008

This paper presents a new navigation algorithm of an autonomous mobile robot with vision and IR sensors, Zigbee Sensor Network using fuzzy rules. We also show that the developed mobile robot with the proposed algorithm is navigating very well in complex unknown environments.

• Proceedings of the Korea Concrete Institute Conference
• /
• 2000.04a
• /
• pp.583-586
• /
• 2000

In this paper, the embedded crack approach that crack is modeled by discontinuous line inside finite element is applied for localized progressive fracture analyses. The algorithm for progressive fracture analyses of concrete structure are enhanced by introducing nonlinear softening curve and unloading algorithm of tension-softening curve which can simulate localized fracture of concrete. The failure analysis results ar compared with existing test results for varification.

• Proceedings of the KIEE Conference
• /
• 2008.07a
• /
• pp.1811-1812
• /
• 2008

This paper represents a absolute position tracking system with sensor fusion and PD-gain. this paper presents an accurate localization method by relative and absolute sensor fusion and PD control for position tracking of mobile robot. we developed a sensor based absolution position tracking and smooth moving algorithm using this algorithm.

• Proceedings of the Korean Information Science Society Conference
• /
• 2010.11a
• /
• pp.99-100
• /
• 2010

• Proceedings of the IEEK Conference
• /
• 2000.06e
• /
• pp.131-133
• /
• 2000

In this paper, we proposed a new method for localizing the independent sources generating the observed EEG based on independent component analysis (ICA). The performance of the algorithm was tested through computer simulations.

• Journal of Radiation Protection and Research
• /
• v.20 no.1
• /
• pp.25-36
• /
• 1995

The purpose of this research is to develop stereotactic localization and radiation measurement system for the efficient and precise radiosurgery. The algorithm to obtain a 3-D stereotactic coordinates of the target has been developed using a Fisher CT or angio localization. The procedure of stereotactic localization was programmed with PC computer, and consists of three steps: (1) transferring patient images into PC; (2) marking the position of target and reference points of the localizer from the patient image; (3) computing the stereotactic 3-D coordinates of target associated with position information of localizer. Coordinate transformation was quickly done on a real time base. The difference of coordinates computed from between Angio and CT localization method was within 2 mm, which could be generally accepted for the reliability of the localization system developed. We measured dose distribution in small fields of NEC 6 MVX linear accelerator using various detector; ion chamber, film, diode. Specific quantities measured include output factor, percent depth dose (PDD), tissue maximum ratio (TMR), off-axis ratio (OAR). There was small variation of measured data according to the different kinds of detectors used. The overall trends of measured beam data were similar enough to rely on our measurement. The measurement was performed with the use of hand-made spherical water phantom and film for standard arc set-up. We obtained the dose distribution as we expected. In conclusion, PC-based 3-D stereotactic localization system was developed to determine the stereotactic coordinate of the target. A convenient technique for the small field measurement was demonstrated. Those methods will be much helpful for the stereotactic radiosurgery.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.18 no.5
• /
• pp.77-87
• /
• 2018

Many researches have been focused on localization in WSNs. However, the solutions for localization in static WSN are hard to apply to the mobile WSN. The solutions for mobile WSN localization have the assumption that there are a significant number of anchor nodes in the networks. In the resource limited situation, these solutions are difficult in applying to the static and mobile mixed WSN. Without using the anchor nodes, a localization service cannot be provided in efficient, accurate and reliable way for mixed wireless sensor networks which have a combination of static nodes and mobile nodes. Also, accuracy is an important consideration for localization in the mixed wireless sensor networks. In this paper, we presented a method to satisfy the requests for the accuracy of the localization without anchor nodes in the wireless sensor networks. Hop coordinates measurements are used as an accurate method for anchor free localization. Compared to the other methods with the same data in the same category, this technique has better accuracy than other methods. Also, we applied a minimum spanning tree algorithm to satisfy the requests for the efficiency such as low communication and computational cost of the localization without anchor nodes in WSNs. The Java simulation results show the correction of the suggested approach in a qualitative way and help to understand the performance in different placements.