The Experts below are selected from a list of 42090 Experts worldwide ranked by ideXlab platform

Min Tan - One of the best experts on this subject based on the ideXlab platform.

  • IEEE ICCI - Vision based navigation for Power Transmission Line inspection robot
    2008 7th IEEE International Conference on Cognitive Informatics, 2008
    Co-Authors: Zize Liang, Zeng-guang Hou, Min Tan
    Abstract:

    Inspection robot must plan its behavior to loose or grasp the Power Transmission Line, or recognize the obstacles from the complex background when it is crawling along the Line in order to negotiate reliably. This paper describes a vision-based navigation system for a Power Line inspection robot. The main emphasis of this paper is on the ability of object recognition. A recognition method based on straight Line extraction is proposed, which is used to recognize the typical obstacles in the Power Transmission Line. Random sample consensus (RANSAC) paradigm is used to group the Line segments. The proposed method scales well with respect to the size of the input image and the number and size of the shapes within the data. Moreover the algorithm is conceptually simple and easy to implement. Experimental results show that good recognition can be achieved using the proposed vision system.

  • IROS - Structure-Constrained Obstacles Recognition for Power Transmission Line Inspection Robot
    2006 IEEE RSJ International Conference on Intelligent Robots and Systems, 2006
    Co-Authors: Yun-chu Zhang, Zize Liang, Zeng-guang Hou, Min Tan, Bo Lian, Qi Zuo
    Abstract:

    Inspection robot must plan its behavior to detect the obstacles from the complex background according to their types when it is crawling along the Power Transmission Line in order to negotiate reliably. However, in most instances, detecting the obstacles from the complex background is a hard task. For this purpose, a novel and fast visual obstacle recognition algorithm is designed based on the structure of the 220 KV Power Transmission Line. Basic principle and architecture of the algorithm are given. By this approach, three typical obstacles on the Power Transmission Line such as insulator strings, counterweights and suspension clamps can be recognized with high accuracy. Experiments in the real Power Transmission Line show its effectiveness. This method can contribute to the process of the mobile robot negotiating obstacles

  • ICIC (2) - Motion deblurring for a Power Transmission Line inspection robot
    Lecture Notes in Computer Science, 2006
    Co-Authors: Yun-chu Zhang, Zize Liang, Zeng-guang Hou, Xiaoguang Zhao, An-min Zou, Min Tan
    Abstract:

    Inspection robot must detect the obstacles from the complex background according to their types when it is crawling along the Power Transmission Line in order to negotiate reliably. In ideal cases, robot's vision system can give satisfactory results, however, motion blur due to camera motion caused by wind or other unknown causes can significantly degrade the quality of the image acquired. It is an undesired effect. In this paper, a complete motion deblurring procedure for obstacle images has been proposed, we try to analyze the running environment of the robot to develop the model of the motion blur. The acquired motion blur information is used to identify the point spread function (PSF) as well as restore the blurred image at the same time. Experiments on real blurred images on Power Transmission Line prove the feasibility and reliability of this algorithm.

Yun-chu Zhang - One of the best experts on this subject based on the ideXlab platform.

  • IROS - Structure-Constrained Obstacles Recognition for Power Transmission Line Inspection Robot
    2006 IEEE RSJ International Conference on Intelligent Robots and Systems, 2006
    Co-Authors: Yun-chu Zhang, Zize Liang, Zeng-guang Hou, Min Tan, Bo Lian, Qi Zuo
    Abstract:

    Inspection robot must plan its behavior to detect the obstacles from the complex background according to their types when it is crawling along the Power Transmission Line in order to negotiate reliably. However, in most instances, detecting the obstacles from the complex background is a hard task. For this purpose, a novel and fast visual obstacle recognition algorithm is designed based on the structure of the 220 KV Power Transmission Line. Basic principle and architecture of the algorithm are given. By this approach, three typical obstacles on the Power Transmission Line such as insulator strings, counterweights and suspension clamps can be recognized with high accuracy. Experiments in the real Power Transmission Line show its effectiveness. This method can contribute to the process of the mobile robot negotiating obstacles

  • ICIC (2) - Motion deblurring for a Power Transmission Line inspection robot
    Lecture Notes in Computer Science, 2006
    Co-Authors: Yun-chu Zhang, Zize Liang, Zeng-guang Hou, Xiaoguang Zhao, An-min Zou, Min Tan
    Abstract:

    Inspection robot must detect the obstacles from the complex background according to their types when it is crawling along the Power Transmission Line in order to negotiate reliably. In ideal cases, robot's vision system can give satisfactory results, however, motion blur due to camera motion caused by wind or other unknown causes can significantly degrade the quality of the image acquired. It is an undesired effect. In this paper, a complete motion deblurring procedure for obstacle images has been proposed, we try to analyze the running environment of the robot to develop the model of the motion blur. The acquired motion blur information is used to identify the point spread function (PSF) as well as restore the blurred image at the same time. Experiments on real blurred images on Power Transmission Line prove the feasibility and reliability of this algorithm.

Zize Liang - One of the best experts on this subject based on the ideXlab platform.

  • IEEE ICCI - Vision based navigation for Power Transmission Line inspection robot
    2008 7th IEEE International Conference on Cognitive Informatics, 2008
    Co-Authors: Zize Liang, Zeng-guang Hou, Min Tan
    Abstract:

    Inspection robot must plan its behavior to loose or grasp the Power Transmission Line, or recognize the obstacles from the complex background when it is crawling along the Line in order to negotiate reliably. This paper describes a vision-based navigation system for a Power Line inspection robot. The main emphasis of this paper is on the ability of object recognition. A recognition method based on straight Line extraction is proposed, which is used to recognize the typical obstacles in the Power Transmission Line. Random sample consensus (RANSAC) paradigm is used to group the Line segments. The proposed method scales well with respect to the size of the input image and the number and size of the shapes within the data. Moreover the algorithm is conceptually simple and easy to implement. Experimental results show that good recognition can be achieved using the proposed vision system.

  • IROS - Structure-Constrained Obstacles Recognition for Power Transmission Line Inspection Robot
    2006 IEEE RSJ International Conference on Intelligent Robots and Systems, 2006
    Co-Authors: Yun-chu Zhang, Zize Liang, Zeng-guang Hou, Min Tan, Bo Lian, Qi Zuo
    Abstract:

    Inspection robot must plan its behavior to detect the obstacles from the complex background according to their types when it is crawling along the Power Transmission Line in order to negotiate reliably. However, in most instances, detecting the obstacles from the complex background is a hard task. For this purpose, a novel and fast visual obstacle recognition algorithm is designed based on the structure of the 220 KV Power Transmission Line. Basic principle and architecture of the algorithm are given. By this approach, three typical obstacles on the Power Transmission Line such as insulator strings, counterweights and suspension clamps can be recognized with high accuracy. Experiments in the real Power Transmission Line show its effectiveness. This method can contribute to the process of the mobile robot negotiating obstacles

  • ICIC (2) - Motion deblurring for a Power Transmission Line inspection robot
    Lecture Notes in Computer Science, 2006
    Co-Authors: Yun-chu Zhang, Zize Liang, Zeng-guang Hou, Xiaoguang Zhao, An-min Zou, Min Tan
    Abstract:

    Inspection robot must detect the obstacles from the complex background according to their types when it is crawling along the Power Transmission Line in order to negotiate reliably. In ideal cases, robot's vision system can give satisfactory results, however, motion blur due to camera motion caused by wind or other unknown causes can significantly degrade the quality of the image acquired. It is an undesired effect. In this paper, a complete motion deblurring procedure for obstacle images has been proposed, we try to analyze the running environment of the robot to develop the model of the motion blur. The acquired motion blur information is used to identify the point spread function (PSF) as well as restore the blurred image at the same time. Experiments on real blurred images on Power Transmission Line prove the feasibility and reliability of this algorithm.

Zeng-guang Hou - One of the best experts on this subject based on the ideXlab platform.

  • IEEE ICCI - Vision based navigation for Power Transmission Line inspection robot
    2008 7th IEEE International Conference on Cognitive Informatics, 2008
    Co-Authors: Zize Liang, Zeng-guang Hou, Min Tan
    Abstract:

    Inspection robot must plan its behavior to loose or grasp the Power Transmission Line, or recognize the obstacles from the complex background when it is crawling along the Line in order to negotiate reliably. This paper describes a vision-based navigation system for a Power Line inspection robot. The main emphasis of this paper is on the ability of object recognition. A recognition method based on straight Line extraction is proposed, which is used to recognize the typical obstacles in the Power Transmission Line. Random sample consensus (RANSAC) paradigm is used to group the Line segments. The proposed method scales well with respect to the size of the input image and the number and size of the shapes within the data. Moreover the algorithm is conceptually simple and easy to implement. Experimental results show that good recognition can be achieved using the proposed vision system.

  • IROS - Structure-Constrained Obstacles Recognition for Power Transmission Line Inspection Robot
    2006 IEEE RSJ International Conference on Intelligent Robots and Systems, 2006
    Co-Authors: Yun-chu Zhang, Zize Liang, Zeng-guang Hou, Min Tan, Bo Lian, Qi Zuo
    Abstract:

    Inspection robot must plan its behavior to detect the obstacles from the complex background according to their types when it is crawling along the Power Transmission Line in order to negotiate reliably. However, in most instances, detecting the obstacles from the complex background is a hard task. For this purpose, a novel and fast visual obstacle recognition algorithm is designed based on the structure of the 220 KV Power Transmission Line. Basic principle and architecture of the algorithm are given. By this approach, three typical obstacles on the Power Transmission Line such as insulator strings, counterweights and suspension clamps can be recognized with high accuracy. Experiments in the real Power Transmission Line show its effectiveness. This method can contribute to the process of the mobile robot negotiating obstacles

  • ICIC (2) - Motion deblurring for a Power Transmission Line inspection robot
    Lecture Notes in Computer Science, 2006
    Co-Authors: Yun-chu Zhang, Zize Liang, Zeng-guang Hou, Xiaoguang Zhao, An-min Zou, Min Tan
    Abstract:

    Inspection robot must detect the obstacles from the complex background according to their types when it is crawling along the Power Transmission Line in order to negotiate reliably. In ideal cases, robot's vision system can give satisfactory results, however, motion blur due to camera motion caused by wind or other unknown causes can significantly degrade the quality of the image acquired. It is an undesired effect. In this paper, a complete motion deblurring procedure for obstacle images has been proposed, we try to analyze the running environment of the robot to develop the model of the motion blur. The acquired motion blur information is used to identify the point spread function (PSF) as well as restore the blurred image at the same time. Experiments on real blurred images on Power Transmission Line prove the feasibility and reliability of this algorithm.

Qi Zuo - One of the best experts on this subject based on the ideXlab platform.

  • IROS - Structure-Constrained Obstacles Recognition for Power Transmission Line Inspection Robot
    2006 IEEE RSJ International Conference on Intelligent Robots and Systems, 2006
    Co-Authors: Yun-chu Zhang, Zize Liang, Zeng-guang Hou, Min Tan, Bo Lian, Qi Zuo
    Abstract:

    Inspection robot must plan its behavior to detect the obstacles from the complex background according to their types when it is crawling along the Power Transmission Line in order to negotiate reliably. However, in most instances, detecting the obstacles from the complex background is a hard task. For this purpose, a novel and fast visual obstacle recognition algorithm is designed based on the structure of the 220 KV Power Transmission Line. Basic principle and architecture of the algorithm are given. By this approach, three typical obstacles on the Power Transmission Line such as insulator strings, counterweights and suspension clamps can be recognized with high accuracy. Experiments in the real Power Transmission Line show its effectiveness. This method can contribute to the process of the mobile robot negotiating obstacles