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This paper investigates the active observation and mapping of the mobile robot in SLAM problem. Firstly, based on factored solution to the simultaneous localization and mapping (FastSLAM), we apply the approximately optimal particle filter in the sense of statistics, as well as the unscented Kalman filter (UKF) to estimate the configuration of the robot and the position of the landmarks respectively...
It is usually accepted that UKF can be used in the form of state non-expansion when noise is additive, in order to prove it incorrect, we made use of scaled symmetric set unscented transformation to deduce and explain the difference in the situation of complicated additive noise model, theory deduction results indicated there were differences between expansion and non-expansion UKF algorithms while...
This paper focuses the multi-robot cooperative simultaneous localization and mapping (SLAM) problem. First, we proposed a decoupled fashion of the map building. Through this fashion, each robot builds the local sub-map independently. The sub-map fusion approach based on Extended Kalman Filter (EKF) is provided. Second, we implemented the active motion of each robot during the local sub-map building...
This paper investigates the on-line autonomous distribution for landmarks and the active exploration in environment without or lack of landmarks/features, such as disaster conditions and polar region. In such situation, the robot enters the environment carrying some landmarks and distributes them according to the rules given in this paper. The utility of the landmark distribution is analyzed. Then,...
This paper investigates the active simultaneous localization and mapping (SLAM) for mobile robot in unknown environment. Based on the estimation by extended Kalman filter (EKF), we convert the active SLAM into a problem of multi-objective optimal control. The robot chooses the control inputs that optimize the objective function such that it can explore the environment by active, intelligent and adaptive...
In this paper, the method for the simultaneous localization and mapping (SLAM) problem based on extended Kalman filter (EKF) is introduced. Then a strategy of active SLAM using optimal control is proposed. In our method, the accuracy and integrity of localization and mapping constitute the objective function. The robot executes the control inputs which can optimize the function in order to implement...
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