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- W1967732830 abstract "This paper presents a practical real-time visual navigation system, including a vision system, a particle filter (PF) based localization system, and a path planning system, for humanoid robots in an indoor environment. A neural network (NN) converter system is used to solve the image distortion problem. The monocular vision system detects objects of interest in the scene, calculating their position in the image, and converting the position in the image to real world coordinates. The PF localization system estimates the current position by the robot’s motion model and corrects the estimated position by using feedback from the data gathered by the vision system. The path planning system determines the next motion based on the result of the localization system. This paper uses a tree-like path planning method which not only guides the robot to the destination but also avoids obstacles at the same time. The navigation method allows a user to assign several different target destinations to the robot simultaneously. The proposed method is implemented on a humanoid robot “ROBOTIS DARwIn-OP”, an open platform humanoid robot. The effectiveness of the system is demonstrated in an empirical evaluation." @default.
- W1967732830 created "2016-06-24" @default.
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- W1967732830 date "2013-01-01" @default.
- W1967732830 modified "2023-09-27" @default.
- W1967732830 title "Real-Time Navigation for a Humanoid Robot Using Particle Filter" @default.
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- W1967732830 doi "https://doi.org/10.4028/www.scientific.net/amm.284-287.1914" @default.
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