• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1254-1257
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• 1993

Presented in this paper is a newly developed motion planning method of an autonomous mobile robot(MAR) which can be applied to flexible manufacturing systems(FMS). The mobile robot is designed for transporting tools and workpieces between a set-up station and machines according to production schedules of the whole FMS. The proposed method is implemented based on an earlier developed real-time obstacle avoidance method which employs Kohonen network for pattern classification of sonar readings and fuzzy logic for local path planning. Particulary, a novel obstacle avoidance method for moving objects using a collision index, collision possibility measure, is described. Our method has been tested on the SNU mobile robot. The experimental results show that the robot successfully navigates to its target while avoiding moving objects.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.83-86
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• 1987

A vision algorithm is presented for the separation of near objects from distant objects. In the algorithm, a difference field of a stereo pair of images is computed to obtain the range information and the median filter is used for the suppression of distant objects. The objects within a given distance is segmented by thresholding the gray scale cross-section of the median filtered difference field. The experiment is performed in a laboratory setting.

• Journal of Internet Computing and Services
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• v.8 no.2
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• pp.1-13
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• 2007

GPS/GIS and RFID technologies have been changing the paradigm af our society toward ubiquitous era. Especially, geographically distributed mobile agents with transporting objects need to be automatically recognizable and traceable under certain conditions. To do this, fundamental theories and technologies are required to specify and verify spatial and temporal behaviors of agents on geographical space. This paper presents a new formal method, called Calculus of Real-Time Distribution, Mobility, and Interaction (CaRDMI), for this purpose. For specification, CaRDMI defines a map, mobile agents with transporting objects. The movement of on agent is represented by a path on the map, consisting of a list of nodes and a list of edges with spatial and temporal constraints. Interactive constraints among agents are represented by synchronization modes on objects at nodes. These constraints are distinguishable features of CaRDMI from other methods. Especially, many-to-many timed synchronization constraints are noticeable. For verification, CaRDMI presents the spatial, temporal and interactive deduction rules and the spatial and temporal equivalence relations.

• Journal of Internet Computing and Services
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• v.9 no.4
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• pp.115-131
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• 2008

Small mobile devices have become commonplace in our everyday life, from cellular phones to PDAs. Discovering dense regions for the mobile devices is one of the problems of grate practical importance. It can be used in monitoring movement of vehicles, concentration of troops, etc. In this paper, we propose a novel algorithm on continuously clustering a large set of mobile objects. We assume that a mobile object reports its position only if it is too far away from the expected position and thus the location data received may be imprecise. To compute the location of each individual object could be costly especially when the number of objects is large. To reduce the complexity of the computation, we want to first cluster objects that are in proximity into a group and treat the members in a group indistinguishable. Each individual object will be examined only when the inaccuracy causes ambiguity in the final results. We conduct extensive experiments on various data sets and analyze the sensitivity and scalability of our algorithms.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.49.6-49
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• 2001

This paper describes a self-localization method for the mobile robot using panoramic view images. A panoramic view image has the information of location of the objects from the viewer robot and direction between the objects at a position. Among the sequence of panoramic view images, the target objects in the image like traffic signs, facade of a building, road signs, etc. locate in the real world so that robot´s position and direction deliver to localize from his view. With the previously captured panoramic images, the method calculates the distance and direction of the region of interest, corresponds the regions between the sequences, and identifies the location in the world. To obtain the region, vertical edge line segments

• Journal of Internet Computing and Services
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• v.16 no.4
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• pp.25-37
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• 2015

This study has developed a mobile AR contents Builder (MARB) featuring the augmentation of virtual objects, e. g. 2D images, 3D models and videos on user-preferred markers in mobile environment and with connected interaction events. The developed MARB is capable of augmenting multiple virtual objects on markers preferred by users, and selectively supporting many marker-specific interaction events. The MARB is also developed as a mobile App for convenience of use in the mobile environment. This makes users to implement AR contents by a GUI-based authoring procedure on the mobile device. The developed MARB allows App developers and general users to author mobile contents easily and can be applied to various field by those who wish to use diverse mobile AR contents. Moreover, the MARB will provide solutions for the expansion of mobile AR market, by overcoming the difficulties of mobile AR content development.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.4
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• pp.365-371
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• 2009

A intelligent mobile hexapod robot with various types of sensors and wireless camera is introduced. We show this mobile robot can detect objects well by combining the results of active sensors and image processing algorithm. First, to detect objects, active sensors such as infrared rays sensors and supersonic waves sensors are employed together and calculates the distance in real time between the object and the robot using sensor's output. The difference between the measured value and calculated value is less than 5%. This paper suggests effective visual detecting system for moving objects with specified color and motion information. The proposed method includes the object extraction and definition process which uses color transformation and AWUPC computation to decide the existence of moving object. We add weighing values to each results from sensors and the camera. Final results are combined to only one value which represents the probability of an object in the limited distance. Sensor fusion technique improves the detection rate at least 7% higher than the technique using individual sensor.

• The Journal of Korea Robotics Society
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• v.3 no.2
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• pp.91-98
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• 2008

This paper describes the recognition method of moving objects in mobile robot with an omnidirectional camera. The moving object is detected using the specific pattern of an optical flow in omnidirectional image. This paper consists of two parts. In the first part, the pattern of an optical flow is investigated in omnidirectional image. The optical flow in omnidirectional image is influenced on the geometry characteristic of an omnidirectional camera. The pattern of an optical flow is theoretically and experimentally investigated. In the second part, the detection of moving objects is presented from the estimated optical flow. The moving object is extracted through the relative evaluation of optical flows which is derived from the pattern of optical flow. In particular, Focus-Of-Expansion (FOE) and Focus-Of-Contraction (FOC) vectors are defined from the estimated optical flow. They are used as reference vectors for the relative evaluation of optical flows. The proposed algorithm is performed in four motions of a mobile robot such as straight forward, left turn, right turn and rotation. Experimental results using real movie show the effectiveness of the proposed method.

• Journal of Information Processing Systems
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• v.16 no.5
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• pp.1214-1222
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• 2020

Pervasive augmented reality (AR) technology can be used to efficiently search for the required information regarding products in stores through text augmentation in an Internet of Things (IoT) environment. The evolution of context awareness and image processing technologies are the main driving forces that realize this type of AR service. One of the problems to be addressed in the service is that augmented objects are fixed and cannot be replaced efficiently in real time. To address this problem, a real-time mobile AR framework is proposed. In this framework, an optimal object to be augmented is selected based on object similarity comparison, and the augmented objects are efficiently managed using distributed metadata servers to adapt to the user requirements, in a given situation. To evaluate the feasibility of the proposed framework, a prototype system was implemented, and a qualitative evaluation based on questionnaires was conducted. The experimental results show that the proposed framework provides a better user experience than existing features in smartphones, and through fast AR service, the users are able to conveniently obtain additional information on products or objects.

• Spatial Information Research
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• v.14 no.2 s.37
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• pp.235-244
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• 2006

The MMS(Mobile Mapping System) using the vehicle equipped GPS, IMU and CCD Cameras is the effective system for the management of the road facilities, update of the digital map, and etc. The image, vehicle's 3 dimensional position and attitude information provided MMS is a important source for positioning objects included the image. In this research we applied the tracking technique to the specific object in image. The extraction of important object from immense MMS data makes more effectiveness in this system.