Self-localization Based on Kalman Filter and Monte Carlo Fusion of Odometry and Visual Information
نویسندگان
چکیده
The main goal of this paper is to describe the application of two self-localization methods, based on Kalman filter and Monte Carlo fusion of odometry and visual information, to omni-directional soccer robots. The two methods are compared, and the usage of several candidates for the robot posture, provided by the vision-based observation step, is discussed. Simulated and real robot results are presented.
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