• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.6
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• pp.852-862
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• 2013

This paper proposes a target tracking control method for wheeled mobile robots with nonholonomic constraints by using a backstepping-like feedback linearization. For the target tracking, we apply a vision system to mobile robots to obtain the relative posture information between the mobile robot and the target. The robots do not use the sensors to obtain the velocity information in this paper and therefore assumed the unknown velocities of both mobile robot and target. Instead, the proposed method uses only the maximum velocity information of the mobile robot and target. First, the pseudo command for the forward linear velocity and the heading direction angle are designed based on the kinematics by using the obtained image information. Then, the actual control inputs are designed to make the actual forward linear velocity and the heading direction angle follow the pseudo commands. Through simulations and experiments for the mobile robot we have confirmed that the proposed control method is able to track target even when the velocity sensors are not used at all.

• Journal of Korea Multimedia Society
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• v.13 no.11
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• pp.1630-1642
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• 2010

Recently, there is an increasing need for developing the technique of Hand Gesture Recognition (HGR), for vision based interface. Since hand gesture is defined as consecutive change of hand posture, developing the algorithm of Hand Posture Recognition (HPR) is required. Among the factors that decrease the performance of HPR, we focus on rotation factor. To achieve rotation invariant HPR, we propose a method that uses the property of video that adjacent frames in video have high correlation, considering the environment of HGR. The proposed method introduces template update of object tracking using the above mentioned property, which is different from previous works based on still images. To compare our proposed method with previous methods such as template matching, PCA and LBP, we performed experiments with video that has hand rotation. The accuracy rate of the proposed method is 22.7%, 14.5%, 10.7% and 4.3% higher than ordinary template matching, template matching using KL-Transform, PCA and LBP, respectively.

• Journal of Drive and Control
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• v.17 no.4
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• pp.8-14
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• 2020

Intelligent devices using ICT technology have been introduced in the field of construction machinery to improve productivity and stability. Among the intelligent devices, Machine Guidance is a device that provides real-time posture, location, and work range to drivers by installing various sensors, controllers, and satellite navigation systems on construction machines. Conversely, the efficiency of equipment that requires location information, such as machine guidance, will be greatly reduced in buildings, and tunnels in the GPS blind spots. Thus, the other high-precision positioning technologies are required in the GPS blind spot zone. In this study, we will develop a relative position measurement system that provides precise location information such as construction machinery and robots in a local area where the GPS reception is difficult. A relative position measurement system tracks a marker in the form of a sphere installed on a vehicle by using the image base tracking technology, and measures the distance and direction information to the marker to calculate a position.

• The Journal of the Korea Contents Association
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• v.20 no.3
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• pp.424-431
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• 2020

This paper focused on the development of sports robot that detects a human player and shots a serve ball automatically. When robot technologies apply to the sports machine, the domain problems occurs such as outdoor environments and playing condition to recognize the visual and the vocal modalities. Gaussian mixture model and Kalman filter are used to detect the player's position in the left, right, and depth direction and to avoid the noises caused by the player's posture variation around the net. The sports robot is designed by the pan-tilt structure to shot a serve ball by pneumatic control under the multi layered software architecture. Finally, the proposed tracking and the machine performance are discussed by experimental results.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.4
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• pp.71-76
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• 2019

Research on indoor location tracking technology using smartphone is actively being carried out. Especially, the movement distance of the smartphone should be accurately measured and the movement route of the user should be displayed on the map. Location tracking technology using sensors mounted on smart phones has been used for a long time, but accuracy is not good enough to measure the moving distance of the user using only the sensor. Therefore, when the user moves the smartphone in a certain posture, it must research and develop an appropriate algorithm to measure the distance accurately. In this paper, we propose a method to reduce moving distance estimation error by removing user 's foot shape by limiting the screen of smartphone in pyramid - based optical flow estimation method.

• Journal of the Korea Society of Computer and Information
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• v.25 no.5
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• pp.19-26
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• 2020

This paper proposes a framework for creating acrobatic scenes such as soccer ball lifting using various users' videos. The proposed method can generate a desired result within a few seconds using a general video of user recorded with a mobile phone. The framework of this paper is largely divided into three parts. The first is to analyze the posture by receiving the user's video. To do this, the user can calculate the pose of the user by analyzing the video using a deep learning technique, and track the movement of a selected body part. The second is to analyze the movement trajectory of the selected body part and calculate the location and time of hitting the object. Finally, the trajectory of the object is generated using the analyzed hitting information. Then, a natural object lifting scenes synchronized with the input user's video can be generated. Physical-based optimization was used to generate a realistic moving object. Using the method of this paper, we can produce various augmented reality applications.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.670-673
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• 1999

In this paper, we present a robust motion controller based on Adaptive-Fuzzy technique is proposed that multifunctional vehicle(MVR) for two DOF mobile robot can perform detailed inspection of physical conditions of sewage pipes as well as can effectively repair the damaged portions of the inner walls. The main difficulties in controlling this multifunctional robot vehicles lie in the fact that vehicles usually have three degrees of freedom in position and orientation in spite of having only two degrees of freedom for motion control in tracking mode. Decomposition of error between the reference posture and the current posture makes control of speed and steering possible. The Gyro compass part and Inclonometer of the robot is configured in order to realize position of robot. The proposed Adaptive-Fuzzy motion controller has two main characteristics: The one guarantees that the MVR follows the reference trajectory; the other one compensates the dynamics of the MVR. Simulation results are provided to validate the proposed controller. Experiments have been used to verify the effectiveness and robustness of the motion controller.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1777-1778
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• 2007

In this paper, We design and implement a humanoid robot, With Educational purpose, which can collaborate and communicate with human. We present an affective human-robot communication system for a humanoid robot, D2, which we designed to communicate with a human through dialogue. D2 communicates with humans by understanding and expressing emotion using facial expressions, voice, gestures and posture. Interaction between a human and a robot is made possible through our affective communication framework. The framework enables a robot to catch the emotional status of the user and to respond appropriately. As a result, the robot can engage in a natural dialogue with a human. According to the aim to be interacted with a human for voice, gestures and posture, the developed Educational humanoid robot consists of upper body, two arms, wheeled mobile platform and control hardware including vision and speech capability and various control boards such as motion control boards, signal processing board proceeding several types of sensors. Using the Educational humanoid robot D2, we have presented the successful demonstrations which consist of manipulation task with two arms, tracking objects using the vision system, and communication with human by the emotional interface, the synthesized speeches, and the recognition of speech commands.

• Journal of the Korea Society of Computer and Information
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• v.18 no.5
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• pp.53-60
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• 2013

This paper proposed visualization tool for motion of snowboarding using Skeleton data obtained by the Microsoft's Kinect sensor. The BBP(Balanced Body Position) posture is a most basic motion in the Snowboarding. This posture is the primary technology for stable turns. The implementation of visualization tool to analyse the BBP posture of snowboard. comparative analysis with standard postures to the ankles, knees, hips and spine angle of joints and body tracking using coordinate information obtained by the Kinect Sensor. Analysis of the final results of the screen through the OpenGL library. This research result could be used to analysis for turn postures of snowboarding.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.107-113
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• 2023

This paper proposes a method for detecting smoking behavior in images using artificial intelligence technology. Since smoking is not a static phenomenon but an action, the object detection technology was combined with the posture estimation technology that can detect the action. A smoker detection learning model was developed to detect smokers in images, and the characteristics of smoking behaviors were applied to posture estimation technology to detect smoking behaviors in images. YOLOv8 was used for object detection, and OpenPose was used for posture estimation. In addition, when smokers and non-smokers are included in the image, a method of separating only people was applied. The proposed method was implemented using Google Colab NVIDEA Tesla T4 GPU in Python, and it was found that the smoking behavior was perfectly detected in the given video as a result of the test.