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- W2999309045 abstract "In this paper, a new cooperative range-only simultaneous localization and mapping (RO-SLAM) algorithm is proposed, based on the Rao-Blackwellized particle filter (RBPF). The proposed cooperative approach, which measures ranges between any pair of two nodes cooperatively for the localization, has several advantages over the conventional RBPF based RO-SLAM algorithm. Firstly, the particle distribution with the importance weight can be quickly converged to the Gaussian distribution, which yields a fast convergence with the reduced computational burden. Secondly, the proposed algorithm using the inter-node measurements can yield improved localization accuracy. Thirdly, the accuracy is not affected by odometry error unlike the conventional RO-SLAM algorithm because the map estimation is done without moving a robot, and thus the accuracy level is maintained regardless of the sensor network size. These advantages of the proposed algorithm are verified through several real experiments." @default.
- W2999309045 created "2020-01-23" @default.
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- W2999309045 date "2019-10-01" @default.
- W2999309045 modified "2023-09-25" @default.
- W2999309045 title "Cooperative Range-Only SLAM based on Rao-Blackwellized Particle Filter" @default.
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- W2999309045 doi "https://doi.org/10.1109/sensors43011.2019.8956791" @default.
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