• Journal of Institute of Control, Robotics and Systems
• /
• v.17 no.3
• /
• pp.206-210
• /
• 2011

Vision-based robot localization is challenging due to the vast amount of visual information available, requiring extensive storage and processing time. To deal with these challenges, we propose the use of features extracted from omni-directional panoramic images and present a method for localization of a mobile robot equipped with an omni-directional camera. The core of the proposed scheme may be summarized as follows : First, we utilize an omni-directional camera which can capture instantaneous $360^{\circ}$ panoramic images around a robot. Second, Nodes around the robot are extracted by the correlation coefficients of Circular Horizontal Line between the landmark and the current captured image. Third, the robot position is determined from the locations by the proposed correlation-based landmark image matching. To accelerate computations, we have assigned the node candidates using color information and the correlation values are calculated based on Fast Fourier Transforms. Experiments show that the proposed method is effective in global localization of mobile robots and robust to lighting variations.

• International Journal of Computer Science & Network Security
• /
• v.21 no.9
• /
• pp.203-211
• /
• 2021

Image tampering detection and localization have become an active area of research in the field of digital image forensics in recent times. This is due to the widespread of malicious image tampering. This study presents a new method for image tampering detection and localization that combines the advantages of dilated convolution, residual network, and UNET Architecture. Using the UNET architecture as a backbone, we built the proposed network from two kinds of residual units, one for the encoder path and the other for the decoder path. The residual units help to speed up the training process and facilitate information propagation between the lower layers and the higher layers which are often difficult to train. To capture global image tampering artifacts and reduce the computational burden of the proposed method, we enlarge the receptive field size of the convolutional kernels by adopting dilated convolutions in the residual units used in building the proposed network. In contrast to existing deep learning methods, having a large number of layers, many network parameters, and often difficult to train, the proposed method can achieve excellent performance with a fewer number of parameters and less computational cost. To test the performance of the proposed method, we evaluate its performance in the context of four benchmark image forensics datasets. Experimental results show that the proposed method outperforms existing methods and could be potentially used to enhance image tampering detection and localization.

• Asian Journal of Innovation and Policy
• /
• v.10 no.1
• /
• pp.132-154
• /
• 2021

A mega sport event as the globalization phenomenon is not only the symbol of the process of modernization but also the vehicle to upgrade global power and hold a dominant position in the world competition under the post-industrial era. This study notifies the role of mega sport events as a strategy for urban innovation in the context of global and local. Comparing the different roles of mega sport events between developing countries and developed countries, we intend to answer two questions: 1) what explains the nature and role of mega sport event, and 2) what are the major evidences of the transition in the globalization era. The conceptual framework, based on the temporal and spatial perspective, provides the mechanism through which the strategy for urban innovation has been changed from 'motivation for modernization' to 'rethinking of localization.' Focusing on the case of Seoul, we also compare major issues between two phases: role of agent, urban form, and urban development. Finally, this study sheds light on the concept of 'glocalization' which means the convergence of globalization and localization; and suggests the roles of (local) agent for hosting mega sport events.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.48 no.6
• /
• pp.82-90
• /
• 2011

This paper proposes an advanced outdoor localization algorithm of a GPS(global positioning system)-INS(inertial navigation system) integration system. In order to reduce noise from the internal INS sensors, discrete wavelet transform and variable threshold method are utilized. The UPF (unscented particle filter) combines GPS information and INS signals to implement precise outdoor localization algorithm and to reduce noise caused by the acceleration, deceleration, and unexpected slips. The conventional de-noising method is mainly carried out using a low pass filter and a high pass filter which essentially result in signal distortions. This newly proposed system utilizes the vibration information of actuator according to fluctuations of the velocity to minimize signal distortions. The UPF also resolves non-linearities of the actuator and non-normal distributions of noises. Effectiveness of the proposed algorithm has been verified through the real experiments and the results are demonstrated.

• Tunnel and Underground Space
• /
• v.32 no.3
• /
• pp.231-242
• /
• 2022

In this study, we developed a robot operating system (ROS)-based autonomous driving robot that estimates the robot's position in underground mines and drives and returns through multiple waypoints. Autonomous driving robots utilize SLAM (Simultaneous Localization And Mapping) technology to generate global maps of driving routes in advance. Thereafter, the shape of the wall measured through the LiDAR sensor and the global map are matched, and the data are fused through the AMCL (Adaptive Monte Carlo Localization) technique to correct the robot's position. In addition, it recognizes and avoids obstacles ahead through the LiDAR sensor. Using the developed autonomous driving robot, experiments were conducted on indoor experimental sites that simulated the underground mine site. As a result, it was confirmed that the autonomous driving robot sequentially drives through the multiple waypoints, avoids obstacles, and returns stably.

• Korean Management Science Review
• /
• v.28 no.3
• /
• pp.125-141
• /
• 2011

We have recently witnessed many of global companies did not successfully adapt themselves to local markets, and finally exited the markets experiencing failures. The purpose of this study is to suggest practical glocalization strategies for global e-service companies to run their respective businesses in local markets with success. Glocalization is a terminology blending globalization and localization, meaning that global companies adapt themselves to local cultures, environment, languages, laws and regulations so as to survive and prosper in those markets while maintaining high quality of standards and processes they originally have for global competitive edge. Examining success stories as well as failure ones of global e-service companies having entered Asian markets, we provide marketing mix strategy for successful glocalization, and suggest some guidelines for prospective e-service companies wishing to enter local markets with different cultures and languages to fit themselves to new environments.

• 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.

• Proceedings of the KIEE Conference
• /
• 2004.11c
• /
• pp.493-495
• /
• 2004

In this paper, shows a research in accordance with the design the implementation of the localization system for mobile robot using INS(Inertial Navigation System) and GPS(Global Positioning System). First, a Strapdown Inertial Navigation System : SDINS is designed and implemented for low speed walking robot, by modifying Inertial Navigation System which is widely used for rocket, airplane, ship and so on. In addition, thesis proposes the localization of robot with the method of loosely coupled method by using Kalman Filter with INS/GPS integrated system to utilize assumed position and steed data from GPS.

• Proceedings of the KIEE Conference
• /
• 2011.07a
• /
• pp.1844-1845
• /
• 2011

In this paper, we compared several localization methods for indoor mobile robot navigation using a global ultrasonic sensor network. To estimate the pose of mobile robot in the sensor network, the range or range difference information with or without robot kinematics is used. Simulation results showed that the localization methods with robot kinematics have better performances.

• Proceedings of the KIEE Conference
• /
• 2008.10b
• /
• pp.91-92
• /
• 2008

Localization and its applications are very important area of the mobile robot technology. Especially, accurate localization is needed when we move the mobile robot to the goal position. In indoor cases, Global Positioning System(GPS) is not suitable but Radio Frequency Identification(RFID) technology can provide position data to the robot. A proposed algorithm in this paper uses not only odometry data but also RFID data to improve estimation of true position of the robot with the particle filtering.