• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.1 no.1
• /
• pp.1-17
• /
• 2007

This paper proposes and analyzes a scalable and an efficient cluster based group key management protocol by introducing identity based infrastructure for secure communication in mobile wireless sensor networks. To ensure scalability and dynamic re-configurability, the system employs a cluster based approach by which group members are separated into clusters and the leaders of clusters securely communicate with each other to agree on a group key in response to changes in membership and member movements. Through analysis we have demonstrated that our protocol has a high probability of being resilient for secure communication among mobile nodes. Finally, it is established that the proposed scheme is efficient for secure positioning in wireless sensor networks.

• Journal of Institute of Control, Robotics and Systems
• /
• v.11 no.12
• /
• pp.1068-1076
• /
• 2005

In order to increase the autonomous navigation capability of a mobile robot, it is very crucial to develop a method for the robot to be able to recognize a priori hon structured environmental characteristics. This paper proposes an ultrasonic sensor based real-time method for recognizing a priori known structured indoor environmental characteristics like a wall and comer Unlike the methods reported in the literature the information obtained from the sensor can be processed in real-time by extended Kalman filter to update estimations of the position and orientation of robot with respect to known environmental characteristics.

• Journal of Advanced Marine Engineering and Technology
• /
• v.30 no.8
• /
• pp.919-926
• /
• 2006

To move in unknown or uncertain environment, a mobile robot must collect informations from various sensors and use it to construct a representation of the external world. Ultrasonic sensor can provide range data for this purpose in a simple cost-effective way. However conventional ultrasonic sensor system for a mobile robot are not sufficient for environment recognition because of their large beam opening angle, specular reflection. This paper describe on environmental perception algorithm which can solve these problems in case using ultrasonic sensor. The algorithm consist of two parts. One is to solve beam opening angle problem by fusion from multiple ultrasonic sensors. The other is to cope with specular reflection problem in wall line extract, which is based on Hough Transform. Experiments to verify the validity of the proposed algorithm are carried out, and the results are provided at last part in this paper.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 1999.10a
• /
• pp.105-110
• /
• 1999

This paper presents a local obstacle avoidance method for indoor mobile robots using Lane method and velocity Space Command approach. The method locates local obstacles using the information form multi-sensors, such that ultrasonic sensor array and laser scanning sensor. The method uses lane method to determine optimum collision-free heading direction of a robot. Also, it deals with the robot motion dynamics problem to reduce some vibration and guarantee fast movement as well. It yields translational and rotational velocities required to avoid the detected obstacles and to keep the robot heading direction toward goal location as close as possible. For experimental verification of the method, a mobile robot driven by two AC servo motors, equipped with 24 ultrasonic sensor array and laser scanning sensor navigates using the method through a corridor cluttered with obstacle.

• Proceedings of the KIEE Conference
• /
• 2007.10a
• /
• pp.317-318
• /
• 2007

One of the important factors of the autonomous mobile robot is to build a map for surround environment and estimate its localization. This paper suggests a sensor fusion method of laser range finder and monocular vision sensor for the simultaneous localization and map building. The robot observes the comer points in the environment as features using the laser range finder, and extracts the SIFT algorithm with the monocular vision sensor. We verify the improved localization performance of the mobile robot from the experiment.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.6 no.4
• /
• pp.314-320
• /
• 2006

Navigation in environments that are densely cluttered with obstacles is still a challenge for Autonomous Ground Vehicles (AGVs), especially when the configuration of obstacles is not known a priori. Reactive local navigation schemes that tightly couple the robot actions to the sensor information have proved to be effective in these environments, and because of the environmental uncertainties, STSF(Space and Time Sensor Fusion)-based fuzzy behavior systems have been proposed. Realization of autonomous behavior in mobile robots, using STSF control based on spatial data fusion, requires formulation of rules which are collectively responsible for necessary levels of intelligence. This collection of rules can be conveniently decomposed and efficiently implemented as a hierarchy of fuzzy-behaviors. This paper describes how this can be done using a behavior-based architecture. The approach is motivated by ethological models which suggest hierarchical organizations of behavior. Experimental results show that the proposed method can smoothly and effectively guide a robot through cluttered environments such as dense forests.

• Proceedings of the KIEE Conference
• /
• 2003.07d
• /
• pp.2444-2446
• /
• 2003

This paper presents identified locations of obstacles using ultrasonic and vision sensor for mobile robots. An ultrasonic and a vision sensor provide complementary information. To overcome limitations of each sensor, they are combined. To improve effectiveness of detecting of obstacles in image processing, a modified splitting/merging algorithm is proposed. In order to verify effectiveness, proposed algorithm is applied to a mobile robot control system.

• Journal of information and communication convergence engineering
• /
• v.11 no.1
• /
• pp.24-29
• /
• 2013

In this paper, we propose a fuzzy inference model for a navigation algorithm for a mobile robot that intelligently searches goal location in unknown dynamic environments. Our model uses sensor fusion based on situational commands using an ultrasonic sensor. Instead of using the "physical sensor fusion" method, which generates the trajectory of a robot based upon the environment model and sensory data, a "command fusion" method is used to govern the robot motions. The navigation strategy is based on a combination of fuzzy rules tuned for both goal-approach and obstacle-avoidance based on a hierarchical behavior-based control architecture. To identify the environments, a command fusion technique is introduced where the sensory data of the ultrasonic sensors and a vision sensor are fused into the identification process. The result of experiment has shown that highlights interesting aspects of the goal seeking, obstacle avoiding, decision making process that arise from navigation interaction.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2009.05a
• /
• pp.203-206
• /
• 2009

Because the meteorological observation towers are scattered over large area, the collected meteorological data are very sparse. Therefore, the need for data collection on the limited urban areas like a specific building or subway area brings about vest cost which is required to install the corresponding sensors on the areas. Recently, to overcome this problem, the sensor network technique comes to the fore. This paper studies an application to service the meteorological map using mobile phone sensors.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.33 no.5
• /
• pp.455-462
• /
• 2009

This paper presents design concepts of a reconfigurable mobile robot for both of indoor and outdoor applications. A linkage mechanism and wheel-in-motors give the proposed mobile robot various driving modes in maneuver and good adaptability to irregular surface. Since the mobile robot receives multiple sensor signals from odometers and an orientation sensor, states related to the position and the orientation of the mobile robot are optimally estimated by an extended Kalman filter. Simulations and experimental results show that the performance of dead reckoning on estimating the pose of a mobile robot can be improved remarkably by the optimal state observer.