• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.2
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• pp.141-147
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• 2015

In this study, a position control algorithm for an omni-directional mobile robot based on Mecanum wheels was introduced and experimentally evaluated. Multiple ultrasonic sensors were installed around the mobile robot to obtain position feedback. Using the distance of the robot from the wall, the position and orientation of the mobile robot were calculated. In accordance with the omni-directional velocity generation mechanism, the velocity kinematics between the Mecanum wheel and the mobile platform were determined. Based on this formulation, a simple and intuitive position control algorithm was suggested. To evaluate the control algorithm, a test bed composed of artificial walls was designed and implemented. While conventional control algorithms based on normal wheels require additional path planning for two-dimensional planar motion, the omni-directional mobile robot using distance sensors was able to directly follow target positions with the simple proposed position feedback algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.25.1-25
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• 2001

Intelligent Space is a space where many sensors and intelligent devices are distributed. Mobile robots exist in this space as physical agents, which provide human with services. To realize this, human and mobile robots have to approach each other as much as possible. Moreover, it is necessary for them to perform interactions naturally. Thus, it is desirable for a mobile robot to carry out human-affnitive movement. In this research, a mobile robot is controlled by the Intelligent Space through its resources. The mobile robot is controlled to follow walking human as stably and precisely as possible.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.7
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• pp.901-906
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• 2007

Algorithms of path planning and obstacle avoidance are essential to autonomous mobile robots that are working in unknown environments in the real time. This paper presents a new navigation algorithm for an autonomous mobile robot with vision and IR sensors using fuzzy rules. Temporary targets are set up by distance variation method and then the algorithms of trajectory planning and obstacle avoidance are designed using fuzzy rules. In this approach, several digital image processing technique is employed to detect edge of obstacles and the distances between the mobile robot and the obstacles are measured. An autonomous mobile robot with single vision and IR sensors is built up for experiments. We also show that the autonomous mobile robot with the proposed algorithm is navigating very well in complex unknown environments.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.47 no.1
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• pp.67-75
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• 2010

This paper presents localization algorithm for mobile robot in outdoor environment. Outdoor environment includes the uncertainty on the ground. Magnetic sensor or IMU(Inertial Measurement Unit) has been used to estimate robot's heading angle. Two sensor is unavailable because mobile robot is electric car affected by magnetic field. Heading angle estimation algorithm for mobile robot is implemented using gyro sensor module consisting of 1-axis gyro sensors. Localization algorithm applied Extended Kalman filter that utilized GPS and encoder, gyro sensor module. Experiment results show that proposed localization algorithm improve considerably localization performance of mobile robots.

• Journal of the Korean Society of Industry Convergence
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• v.17 no.3
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• pp.151-169
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• 2014

We propose a new technique for autonomous navigation and travelling of mobile robot based on ultrasonic sensors through the narrow labyrinth that leave only distance of a few centimeters on each side between the guides and the robot. In our current implementation the ultrasonic sensor system fires at a rate of 100 ms, that is, each of the 8 sensors fires once during each 100 ms interval. This is a very good firing rate, implemented here for optimal performance. This paper presents an extensively tested and verified solution to the problem of obstacle avoidance. Our solution is based on the optimal placement of ultrasonic sensors at strategic locations around the robot. Both the sensor location and the associated navigation algorithm are defined in such a way that only the accurate radial sonar data is used for accurate travelling.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.159-162
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• 2002

This paper presents a modified localization scheme of a mobile robot. When it navigates, the position error of a robot is increased and doesn't go to a goal point where the robot intends to go at the beginning. The objective of localization is to estimate the position of a robot precisely. Many algorithms were developed and still are being researched for localization of a mobile robot at present. Among them, a localization algorithm named continuous localization proposed by Schultz has some merits on real-time navigation and is easy to be implemented compared to other localization schemes. Continuous Localization (CL) is based on map-matching algorithm with global and local maps using only ultrasonic sensors for making grid maps. However, CL has some problems in the process of searching the best-scored-map, when it is applied to a mobile robot. We here propose fast and powerful map-matching algorithm for localization of a mobile robot by experiments.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.1
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• pp.54-60
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• 2021

AR (Augmented Reality) is a technology that provides virtual content to the real world and provides additional information to objects in real-time through 3D content. In the past, a high-performance device was required to experience AR, but it was possible to implement AR more easily by improving mobile performance and mounting various sensors such as ToF (Time-of-Flight). Also, the importance of mobile augmented reality is growing with the commercialization of high-speed wireless Internet such as 5G. Thus, this paper proposes a system that can provide AR services via GNN (Graph Neural Network) using cameras and sensors on mobile devices. ToF of mobile devices is used to capture depth maps. A 3D point cloud was created using RGB images to distinguish specific colors of objects. Point clouds created with RGB images and Depth Map perform downsampling for smooth communication between mobile and server. Point clouds sent to the server are used for 3D object detection. The detection process determines the class of objects and uses one point in the 3D bounding box as an anchor point. AR contents are provided through app and web through class and anchor of the detected object.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.3
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• pp.537-542
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• 2022

There is a limit to the current indoor air quality (IAQ) monitoring method using fixed sensors and devices. A mobile robot for IAQ monitoring was developed by mounting IAQ monitoring sensors on a small multi-legged robot to minimize vibration and protect the sensors from vibration while robot moves. The developed mobile robot used a simple gait mechanism to enable the robot to move forward, backward, and turns only with the combination of forward and reverse rotation of the two DC motors. Due to the simple gait mechanism, not only IAQ data measurements but also gait motion control were processed using a single Arduino board. Because the mobile robot has small number of electronic components and low power consumption, a relatively low-capacity battery was mounted on the robot to reduce the weight of the battery. The weight of mobile robot is 1.4kg including links, various IAQ sensors, motors, and battery. The gait and turning speed of the mobile robot was measured at 3.75 cm/sec and 14.13 rad/sec. The maximum height where the robot leg could reach was 33 mm, but the mobile robot was able to overcome the bumps up to 24 mm.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10d
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• pp.791-795
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• 2006

하이브리드 센서 네트워크에서 static sensor node들이 초기 배치된 후, coverage-hole을 결정하여, hole을 커버할 mobile sensor node들의 필요한 수 및 위치를 결정하고 배치하는 연구는 상당한 수준에 이르렀다. 그러나 mobile sensor node들을 호출하고 배치하는데 너무 많은 에너지를 소모하고 있다. 본 논문에서는 coverage-hole에서 mobile sensor node들을 호출하기 전에 mobile sensor node들을 최대한 coverage-hole에 가깝게 배치하여, 호출하는데 소요되는 에너지를 획기적으로 절감하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.4
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• pp.344-365
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• 2009

The performance of a tracking system is greatly increased if multiple types of sensors are combined to achieve the objective of the tracking instead of relying on single type of sensor. To conduct the multi-modal tracking, we have previously developed a multi-modal sensor-based tracking model where acoustic sensors mainly track the objects and visual sensors compensate the tracking errors [1]. In this paper, we find a network synchronization problem appearing in the developed tracking system. The problem is caused by the different location and traffic characteristics of multi-modal sensors and non-synchronized arrival of the captured sensor data at a processing server. To effectively deliver the sensor data, we propose a time-based packet aggregation algorithm where the acoustic sensor data are aggregated based on the sampling time and sent to the server. The delivered acoustic sensor data is then compensated by visual images to correct the tracking errors and such a compensation process improves the tracking accuracy in ideal case. However, in real situations, the tracking improvement from visual compensation can be severely degraded due to the aforementioned network synchronization problem, the impact of which is analyzed by simulations in this paper. To resolve the network synchronization problem, we differentiate the service level of sensor traffic based on Weight Round Robin (WRR) scheduling at the routers. The weighting factor allocated to each queue is calculated by a proposed Delay-based Weight Allocation (DWA) algorithm. From the simulations, we show the traffic differentiation model can mitigate the non-synchronization of sensor data. Finally, we analyze expected traffic behaviors of the tracking system in terms of acoustic sampling interval and visual image size.