The Experts below are selected from a list of 68343 Experts worldwide ranked by ideXlab platform
A. Kosaka - One of the best experts on this subject based on the ideXlab platform.
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vision based Navigation by a mobile robot with obstacle avoidance using single camera vision and ultrasonic sensing
International Conference on Robotics and Automation, 1998Co-Authors: I Ohya, A. KosakaAbstract:This paper describes a vision-based Navigation Method in an indoor environment for an autonomous mobile robot which can avoid obstacles. In this Method, the self-localization of the robot is achieved by a model-based vision system, and nonstop Navigation is realized by a retroactive position correction system. Stationary obstacles are avoided with single-camera vision and moving obstacles are detected with ultrasonic sensors. We report on experiments in a hallway using the YAMABICO robot.
Puig Vicenç - One of the best experts on this subject based on the ideXlab platform.
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Hybrid type-2 fuzzy logic obstacle avoidance system based on horn-schunck Method
ICPE Electra Publishing House, 2020Co-Authors: Nadour Mohamed, Boumehraz Mohamed, Cherroun Lakhmissi, Puig VicençAbstract:This paper is concerned with a visual Navigation Method based on type-2 fuzzy logic controllers (T2FLC) and optical flow (OF) approach. A Takagi-Sugeno fuzzy logic controller is used for obstacle avoidance task based on video acquisition and image processing algorithm. To extract information about the environment, the captured image is divided into two parts, the control system uses optical flow values calculated by a Horn-Shunk algorithm to detect and estimate the positions of obstacles. The efficiency of the proposed structure is simulated using Visual Reality Toolbox. The obtained simulation results demonstrate the effectiveness of this autonomous visual Navigation system
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Hybrid type-2 fuzzy logic obstacle avoidance system based on horn-schunck Method
2019Co-Authors: Nadour Mohamed, Boumehraz Mohamed, Cherroun Lakhmissi, Puig VicençAbstract:This paper is concerned with a visual Navigation Method based on type-2 fuzzy logic controllers (T2FLC) and optical flow (OF) approach. A Takagi-Sugeno fuzzy logic controller is used for obstacle avoidance task based on video acquisition and image processing algorithm. To extract information about the environment, the captured image is divided into two parts, the control system uses optical flow values calculated by a Horn-Shunk algorithm to detect and estimate the positions of obstacles. The efficiency of the proposed structure is simulated using Visual Reality Toolbox. The obtained simulation results demonstrate the effectiveness of this autonomous visual Navigation systemPeer ReviewedPostprint (author's final draft
I Ohya - One of the best experts on this subject based on the ideXlab platform.
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vision based Navigation by a mobile robot with obstacle avoidance using single camera vision and ultrasonic sensing
International Conference on Robotics and Automation, 1998Co-Authors: I Ohya, A. KosakaAbstract:This paper describes a vision-based Navigation Method in an indoor environment for an autonomous mobile robot which can avoid obstacles. In this Method, the self-localization of the robot is achieved by a model-based vision system, and nonstop Navigation is realized by a retroactive position correction system. Stationary obstacles are avoided with single-camera vision and moving obstacles are detected with ultrasonic sensors. We report on experiments in a hallway using the YAMABICO robot.
Nadour Mohamed - One of the best experts on this subject based on the ideXlab platform.
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Hybrid type-2 fuzzy logic obstacle avoidance system based on horn-schunck Method
ICPE Electra Publishing House, 2020Co-Authors: Nadour Mohamed, Boumehraz Mohamed, Cherroun Lakhmissi, Puig VicençAbstract:This paper is concerned with a visual Navigation Method based on type-2 fuzzy logic controllers (T2FLC) and optical flow (OF) approach. A Takagi-Sugeno fuzzy logic controller is used for obstacle avoidance task based on video acquisition and image processing algorithm. To extract information about the environment, the captured image is divided into two parts, the control system uses optical flow values calculated by a Horn-Shunk algorithm to detect and estimate the positions of obstacles. The efficiency of the proposed structure is simulated using Visual Reality Toolbox. The obtained simulation results demonstrate the effectiveness of this autonomous visual Navigation system
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Hybrid type-2 fuzzy logic obstacle avoidance system based on horn-schunck Method
2019Co-Authors: Nadour Mohamed, Boumehraz Mohamed, Cherroun Lakhmissi, Puig VicençAbstract:This paper is concerned with a visual Navigation Method based on type-2 fuzzy logic controllers (T2FLC) and optical flow (OF) approach. A Takagi-Sugeno fuzzy logic controller is used for obstacle avoidance task based on video acquisition and image processing algorithm. To extract information about the environment, the captured image is divided into two parts, the control system uses optical flow values calculated by a Horn-Shunk algorithm to detect and estimate the positions of obstacles. The efficiency of the proposed structure is simulated using Visual Reality Toolbox. The obtained simulation results demonstrate the effectiveness of this autonomous visual Navigation systemPeer ReviewedPostprint (author's final draft
Cherroun Lakhmissi - One of the best experts on this subject based on the ideXlab platform.
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Hybrid type-2 fuzzy logic obstacle avoidance system based on horn-schunck Method
ICPE Electra Publishing House, 2020Co-Authors: Nadour Mohamed, Boumehraz Mohamed, Cherroun Lakhmissi, Puig VicençAbstract:This paper is concerned with a visual Navigation Method based on type-2 fuzzy logic controllers (T2FLC) and optical flow (OF) approach. A Takagi-Sugeno fuzzy logic controller is used for obstacle avoidance task based on video acquisition and image processing algorithm. To extract information about the environment, the captured image is divided into two parts, the control system uses optical flow values calculated by a Horn-Shunk algorithm to detect and estimate the positions of obstacles. The efficiency of the proposed structure is simulated using Visual Reality Toolbox. The obtained simulation results demonstrate the effectiveness of this autonomous visual Navigation system
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Hybrid type-2 fuzzy logic obstacle avoidance system based on horn-schunck Method
2019Co-Authors: Nadour Mohamed, Boumehraz Mohamed, Cherroun Lakhmissi, Puig VicençAbstract:This paper is concerned with a visual Navigation Method based on type-2 fuzzy logic controllers (T2FLC) and optical flow (OF) approach. A Takagi-Sugeno fuzzy logic controller is used for obstacle avoidance task based on video acquisition and image processing algorithm. To extract information about the environment, the captured image is divided into two parts, the control system uses optical flow values calculated by a Horn-Shunk algorithm to detect and estimate the positions of obstacles. The efficiency of the proposed structure is simulated using Visual Reality Toolbox. The obtained simulation results demonstrate the effectiveness of this autonomous visual Navigation systemPeer ReviewedPostprint (author's final draft
