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In this paper, a novel methodology is proposed to solve the simultaneous localization and mapping (SLAM) problem of mobile robot with particle filter (PF) algorithm. Compared with Kalman filter (KF) and extended Kalman filter (EKF), PF has a better performance in non-linear non-Gaussian environments. A close-loop updating scheme is developed in which positions of the robot and landmarks are updated...
Sensor-based localization, as one of the essential parts for robot navigation, continues to be a major research focus in mobile robotics. In this paper, we consider a more challenging localization scenario where an autonomous robotic fish localizes itself with onboard sensors (camera and Inertial Measurement Unit(IMU)) in the water. Specifically, an underwater image processing algorithm is introduced...
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