• Title/Summary/Keyword: Mobile Target Tracking

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Adaptive Spatial Coordinates Detection Scheme for Path-Planning of Autonomous Mobile Robot (자율 이동로봇의 경로추정을 위한 적응적 공간좌표 검출 기법)

  • Lee, Jung-Suk;Ko, Jung-Hwan
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.55 no.2
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    • pp.103-109
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    • 2006
  • In this paper, the detection scheme of the spatial coordinates based on stereo camera for a intelligent path planning of an automatic mobile robot is proposed. In the proposed system, face area of a moving person is detected from a left image among the stereo image pairs by using the YCbCr color model and its center coordinates are computed by using the centroid method and then using these data, the stereo camera embedded on the mobile robot can be controlled for tracking the moving target in real-time. Moreover, using the disparity mad obtained from the left and right images captured by the tracking-controlled stereo camera system and the perspective transformation between a 3-D scene. and an image plane, depth information can be detected. Finally, based-on the analysis of these calculated coordinates, a mobile robot system is derived as a intelligent path planning and a estimation.

Implementation and Verification of Deep Learning-based Automatic Object Tracking and Handy Motion Control Drone System (심층학습 기반의 자동 객체 추적 및 핸디 모션 제어 드론 시스템 구현 및 검증)

  • Kim, Youngsoo;Lee, Junbeom;Lee, Chanyoung;Jeon, Hyeri;Kim, Seungpil
    • IEMEK Journal of Embedded Systems and Applications
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    • v.16 no.5
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    • pp.163-169
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    • 2021
  • In this paper, we implemented a deep learning-based automatic object tracking and handy motion control drone system and analyzed the performance of the proposed system. The drone system automatically detects and tracks targets by analyzing images obtained from the drone's camera using deep learning algorithms, consisting of the YOLO, the MobileNet, and the deepSORT. Such deep learning-based detection and tracking algorithms have both higher target detection accuracy and processing speed than the conventional color-based algorithm, the CAMShift. In addition, in order to facilitate the drone control by hand from the ground control station, we classified handy motions and generated flight control commands through motion recognition using the YOLO algorithm. It was confirmed that such a deep learning-based target tracking and drone handy motion control system stably track the target and can easily control the drone.

Tracking and Capturing a Moving Object Using Active Camera Mounted on a Mobile Robot (이동로봇에 장착된 능동 카메라를 이용한 이동물체의 추적과 포획)

  • Park, Jin-U;Park, Jae-Han;Yun, Gyeong-Sik;Lee, Jang-Myeong
    • Journal of Institute of Control, Robotics and Systems
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    • v.7 no.9
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    • pp.741-748
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    • 2001
  • In this paper, we propose a method of tracking and capturing a moving object by a mobile robot. The position of the moving object is acquired from the relation through color-based image information from a 2-DOF active camera mounted on the mobile robot. The direction and rotational angular velocity of the moving object are estimated using a state estimator. A Kalman fiber is used as the state estimator for taking characteristics of robustness against noises and uncertainties included in the input data. After estimating the trajectory of the moving object, we decide on the optimal trajectory and plan the motion of the mobile robot to capture the target object within the shortest distance and time. The effectiveness of the proposed method is demonstrated by the simulations and experiments.

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Fuzzy Tracking Control Based on Stereo Images for Tracking of Moving Robot (이동 로봇 추적을 위한 스테레오 영상기반 퍼지 추적제어)

  • Min, Hyun-Hong;Yoo, Dong-Sang;Kim, Yong-Tae
    • Journal of the Korean Institute of Intelligent Systems
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    • v.22 no.2
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    • pp.198-204
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    • 2012
  • Tracking and recognition of robots are required for the cooperation task of robots in various environments. In the paper, a tracking control system of moving robot using stereo image processing, code-book model and fuzzy controller is proposed. First, foreground and background images are separated by using code-book model method. A candidate region is selected based on the color information in the separated foreground image and real distance of the robot is estimated from matching process of depth image that is acquired through stereo image processing. The open and close processing of image are applied and labeling according to the size of mobile robot is used to recognize the moving robot effectively. A fuzzy tracking controller using distance information and mobile information by stereo image processing is designed for effective tracking according to the movement velocity of the target robot. The proposed fuzzy tracking control method is verified through tracking experiments of mobile robots with stereo camera.

Implementation of Surveillance System using Motion Tracking Method based on Mobile (모바일 기반의 동작 추적 기법을 이용한 감시 시스템의 구현)

  • Kim, Hyeng-Gyun;Kim, Yong-Ho;Guen, Bae-Yong
    • Journal of Advanced Navigation Technology
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    • v.12 no.2
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    • pp.164-169
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    • 2008
  • This paper is using motion tracking by image segmentation to monitor intruders and to confirm based on mobile the relevant information. First, detect frame in animation that film fixed area, and make use of image subtraction between two frame that adjoin, segment fixed backing and target who move. Segmental foreground object to the edge detecting the location specified by the edge of the median estimate extracted by analyzing the motion of the intruders to monitor. When a motion is detected, the detected image is transmitted by using the W AP pull basis image transmission method on the mobile client data terminal.

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Mobile App Recommendation with Sequential App Usage Behavior Tracking

  • Yongkeun Hwang;Donghyeon Lee;Kyomin Jung
    • Journal of Internet Technology
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    • v.20 no.3
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    • pp.827-838
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    • 2019
  • The recent evolution of mobile devices and services have resulted in such plethora of mobile applications (apps) that users have difficulty finding the ones they wish to use in a given moment. We design an app recommendation system which predicts the app to be executed with high accuracy so that users are able to access their next app conveniently and quickly. We introduce the App-Usage Tracking Feature (ATF), a simple but powerful feature for predicting next app launches, which characterizes each app use from the sequence of previously used apps. In addition, our method can be implemented without compromising the user privacy since it is solely trained on the target user's mobile usage data and it can be conveniently implemented in the individual mobile device because of its less computation-intensive behavior. We provide a comprehensive empirical analysis of the performance and characteristics of our proposed method on real-world mobile usage data. We also demonstrate that our system can accurately predict the next app launches and outperforms the baseline methods such as the most frequently used apps (MFU) and the most recently used apps (MRU).

Modeling and Control of Welding Mobile Robot for the Tracking of Lattice Type Welding Seam (격자형 용접선 추적을 위한 용접 이동로봇의 모델링 및 제어)

  • Lee, Gun-You;Suh, Jin-Ho;Oh, Myung-Suk;Kim, Sang-Bong
    • Proceedings of the KSME Conference
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    • 2003.04a
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    • pp.923-928
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    • 2003
  • This paper presents the motion control of a mobile robot with arc sensor for lattice type welding. Its dynamic equation and motion control method for welding speed and seam tracking are described. The motion control is realized in the view of keeping constant welding speed and precise target line even though the robot is driven along a straight line or comer. The mobile robot is modeled based on Lagrange equation under nonholonomic constraints and the model is represented in state space form. The motion control of the mobile robot is separated into three driving motions of straight locomotion, turning locomotion and torch slider controls. For the torch slider control, the proportional integral derivative (PID) control method is used. For the straight locomotion, a concept of decoupling method between input and output is adopted and for the turning locomotion, the turning speed is controlled according to the angular velocity value at each point of the comer with range of $90^{\circ}$ constrained to the welding speed. The proposed control methods are proved through simulation results and the results have proved that the mobile robot has enough ability to apply the lattice type welding line.

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A Study on Intelligence Navigation for Autonomous Mobile Robot Using Fuzzy Logic Control

  • Huh, Dei-Jeung;Lee, Woo-Young;Huh, Uk-Youl
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.138.5-138
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    • 2001
  • The autonomous robot has the ability of obstacle avoidance and target tracking with some manufactured information. In this paper, it is shown that autonomous mobile robot can avoid fixed obstacles using the map made before and the fuzzy controller is adopted with the global path planing and the local path planing when the robot navigates. With that map sensor, information will be used when an autonomous robot navigates. This paper proves that robot can navigate through optimized route and keep the stable condition.

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Implementation of Object Feature Extraction within Image for Object Tracking (객체 추적을 위한 영상 내의 객체 특징점 추출 알고리즘 구현)

  • Lee, Yong-Hwan;Kim, Youngseop
    • Journal of the Semiconductor & Display Technology
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    • v.17 no.3
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    • pp.113-116
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    • 2018
  • This paper proposes a mobile image search system which uses a sensor information of smart phone, and enables running in a variety of environments, which is implemented on Android platform. The implemented system deals with a new image descriptor using combination of the visual feature (CEDD) with EXIF attributes in the target of JPEG image, and image matching scheme, which is optimized to the mobile platform. Experimental result shows that the proposed method exhibited a significant improved searching results of around 80% in precision in the large image database. Considering the performance such as processing time and precision, we think that the proposed method can be used in other application field.

Moving Object Following by a Mobile Robot using a Single Curvature Trajectory and Kalman Filters (단일곡률궤적과 칼만필터를 이용한 이동로봇의 동적물체 추종)

  • Lim, Hyun-Seop;Lee, Dong-Hyuk;Lee, Jang-Myung
    • Journal of Institute of Control, Robotics and Systems
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    • v.19 no.7
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    • pp.599-604
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    • 2013
  • Path planning of mobile robots has a purpose to design an optimal path from an initial position to a target point. Minimum driving time, minimum driving distance and minimum driving error might be considered in choosing the optimal path and are correlated to each other. In this paper, an efficient driving trajectory is planned in a real situation where a mobile robot follows a moving object. Position and distance of the moving object are obtained using a web camera, and the rotation angular and linear velocities are estimated using Kalman filters to predict the trajectory of the moving object. Finally, the mobile robot follows the moving object using a single curvature trajectory by estimating the trajectory of the moving object. Using the estimation by Kalman filters and the single curvature in the trajectory planning, the total tracking distance and time saved amounts to about 7%. The effectiveness of the proposed algorithm has been verified through real tracking experiments.