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The issues of simultaneous localization and mapping (SLAM) and moving target tracking are investigated in this paper. In EKF-based SLAM, the computational complexity significantly increases with the growing number of landmarks to be estimated. To solve this problem, the constrained local submap filter (CLSF) is used in this paper to reduce the computational complexity of SLAM and target tracking....
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...
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...
To solve the range scan matching problem, this paper describes a matching rule for points in polar coordinate, i.e. PPMR (Polar Point Matching Rule), which takes into account both rotation and translation error of the scanner displacement at the same time, and can be applied for both 2D and 3D scans. Based on PPMR, a fast correspondence search algorithm is developed taking advantage of the structure...
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,...
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