The Experts below are selected from a list of 32067 Experts worldwide ranked by ideXlab platform
Meng Li-hang - One of the best experts on this subject based on the ideXlab platform.
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An experimental evaluation of balance strategy based Obstacle Avoidance
2016 14th International Conference on Control, Automation, Robotics and Vision, ICARCV 2016, 2017Co-Authors: Ruijuan Chang, Mengxiang Lin, Dechao Meng, Zeye Wu, Rong Ding, Meng Li-hangAbstract:Optical flow plays an important role in vision-based navigation. A lot of optical flow based methods have been developed for autonomous robots. In this paper, we evaluate Obstacle Avoidance methods based on optical flow in synthetic and real-world scenes. Specifically, the balance strategy is chosen and five representative optical flow algorithms are used. The new metrics for Obstacle Avoidance performance are introduced. Our experiments demonstrate the effectiveness of the balance strategy for Obstacle Avoidance. Furthermore, some factors contributing to Obstacle Avoidance ability are studied.
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ICARCV - An experimental evaluation of balance strategy based Obstacle Avoidance
2016 14th International Conference on Control Automation Robotics and Vision (ICARCV), 2016Co-Authors: Ruijuan Chang, Dechao Meng, Zeye Wu, Rong Ding, Meng Li-hangAbstract:Optical flow plays an important role in vision-based navigation. A lot of optical flow based methods have been developed for autonomous robots. In this paper, we evaluate Obstacle Avoidance methods based on optical flow in synthetic and real-world scenes. Specifically, the balance strategy is chosen and five representative optical flow algorithms are used. The new metrics for Obstacle Avoidance performance are introduced. Our experiments demonstrate the effectiveness of the balance strategy for Obstacle Avoidance. Furthermore, some factors contributing to Obstacle Avoidance ability are studied.
Ruijuan Chang - One of the best experts on this subject based on the ideXlab platform.
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An experimental evaluation of balance strategy based Obstacle Avoidance
2016 14th International Conference on Control, Automation, Robotics and Vision, ICARCV 2016, 2017Co-Authors: Ruijuan Chang, Mengxiang Lin, Dechao Meng, Zeye Wu, Rong Ding, Meng Li-hangAbstract:Optical flow plays an important role in vision-based navigation. A lot of optical flow based methods have been developed for autonomous robots. In this paper, we evaluate Obstacle Avoidance methods based on optical flow in synthetic and real-world scenes. Specifically, the balance strategy is chosen and five representative optical flow algorithms are used. The new metrics for Obstacle Avoidance performance are introduced. Our experiments demonstrate the effectiveness of the balance strategy for Obstacle Avoidance. Furthermore, some factors contributing to Obstacle Avoidance ability are studied.
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ICARCV - An experimental evaluation of balance strategy based Obstacle Avoidance
2016 14th International Conference on Control Automation Robotics and Vision (ICARCV), 2016Co-Authors: Ruijuan Chang, Dechao Meng, Zeye Wu, Rong Ding, Meng Li-hangAbstract:Optical flow plays an important role in vision-based navigation. A lot of optical flow based methods have been developed for autonomous robots. In this paper, we evaluate Obstacle Avoidance methods based on optical flow in synthetic and real-world scenes. Specifically, the balance strategy is chosen and five representative optical flow algorithms are used. The new metrics for Obstacle Avoidance performance are introduced. Our experiments demonstrate the effectiveness of the balance strategy for Obstacle Avoidance. Furthermore, some factors contributing to Obstacle Avoidance ability are studied.
Zeye Wu - One of the best experts on this subject based on the ideXlab platform.
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An experimental evaluation of balance strategy based Obstacle Avoidance
2016 14th International Conference on Control, Automation, Robotics and Vision, ICARCV 2016, 2017Co-Authors: Ruijuan Chang, Mengxiang Lin, Dechao Meng, Zeye Wu, Rong Ding, Meng Li-hangAbstract:Optical flow plays an important role in vision-based navigation. A lot of optical flow based methods have been developed for autonomous robots. In this paper, we evaluate Obstacle Avoidance methods based on optical flow in synthetic and real-world scenes. Specifically, the balance strategy is chosen and five representative optical flow algorithms are used. The new metrics for Obstacle Avoidance performance are introduced. Our experiments demonstrate the effectiveness of the balance strategy for Obstacle Avoidance. Furthermore, some factors contributing to Obstacle Avoidance ability are studied.
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ICARCV - An experimental evaluation of balance strategy based Obstacle Avoidance
2016 14th International Conference on Control Automation Robotics and Vision (ICARCV), 2016Co-Authors: Ruijuan Chang, Dechao Meng, Zeye Wu, Rong Ding, Meng Li-hangAbstract:Optical flow plays an important role in vision-based navigation. A lot of optical flow based methods have been developed for autonomous robots. In this paper, we evaluate Obstacle Avoidance methods based on optical flow in synthetic and real-world scenes. Specifically, the balance strategy is chosen and five representative optical flow algorithms are used. The new metrics for Obstacle Avoidance performance are introduced. Our experiments demonstrate the effectiveness of the balance strategy for Obstacle Avoidance. Furthermore, some factors contributing to Obstacle Avoidance ability are studied.
Dechao Meng - One of the best experts on this subject based on the ideXlab platform.
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An experimental evaluation of balance strategy based Obstacle Avoidance
2016 14th International Conference on Control, Automation, Robotics and Vision, ICARCV 2016, 2017Co-Authors: Ruijuan Chang, Mengxiang Lin, Dechao Meng, Zeye Wu, Rong Ding, Meng Li-hangAbstract:Optical flow plays an important role in vision-based navigation. A lot of optical flow based methods have been developed for autonomous robots. In this paper, we evaluate Obstacle Avoidance methods based on optical flow in synthetic and real-world scenes. Specifically, the balance strategy is chosen and five representative optical flow algorithms are used. The new metrics for Obstacle Avoidance performance are introduced. Our experiments demonstrate the effectiveness of the balance strategy for Obstacle Avoidance. Furthermore, some factors contributing to Obstacle Avoidance ability are studied.
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ICARCV - An experimental evaluation of balance strategy based Obstacle Avoidance
2016 14th International Conference on Control Automation Robotics and Vision (ICARCV), 2016Co-Authors: Ruijuan Chang, Dechao Meng, Zeye Wu, Rong Ding, Meng Li-hangAbstract:Optical flow plays an important role in vision-based navigation. A lot of optical flow based methods have been developed for autonomous robots. In this paper, we evaluate Obstacle Avoidance methods based on optical flow in synthetic and real-world scenes. Specifically, the balance strategy is chosen and five representative optical flow algorithms are used. The new metrics for Obstacle Avoidance performance are introduced. Our experiments demonstrate the effectiveness of the balance strategy for Obstacle Avoidance. Furthermore, some factors contributing to Obstacle Avoidance ability are studied.
Rong Ding - One of the best experts on this subject based on the ideXlab platform.
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An experimental evaluation of balance strategy based Obstacle Avoidance
2016 14th International Conference on Control, Automation, Robotics and Vision, ICARCV 2016, 2017Co-Authors: Ruijuan Chang, Mengxiang Lin, Dechao Meng, Zeye Wu, Rong Ding, Meng Li-hangAbstract:Optical flow plays an important role in vision-based navigation. A lot of optical flow based methods have been developed for autonomous robots. In this paper, we evaluate Obstacle Avoidance methods based on optical flow in synthetic and real-world scenes. Specifically, the balance strategy is chosen and five representative optical flow algorithms are used. The new metrics for Obstacle Avoidance performance are introduced. Our experiments demonstrate the effectiveness of the balance strategy for Obstacle Avoidance. Furthermore, some factors contributing to Obstacle Avoidance ability are studied.
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ICARCV - An experimental evaluation of balance strategy based Obstacle Avoidance
2016 14th International Conference on Control Automation Robotics and Vision (ICARCV), 2016Co-Authors: Ruijuan Chang, Dechao Meng, Zeye Wu, Rong Ding, Meng Li-hangAbstract:Optical flow plays an important role in vision-based navigation. A lot of optical flow based methods have been developed for autonomous robots. In this paper, we evaluate Obstacle Avoidance methods based on optical flow in synthetic and real-world scenes. Specifically, the balance strategy is chosen and five representative optical flow algorithms are used. The new metrics for Obstacle Avoidance performance are introduced. Our experiments demonstrate the effectiveness of the balance strategy for Obstacle Avoidance. Furthermore, some factors contributing to Obstacle Avoidance ability are studied.
