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Decentralized Cooperative Localization with Fault Detection and Isolation in Robot Teams

Mei Wu, Hongbin Ma, Xinghong Zhang

发表年份
2018
引用次数
13
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摘要

Robot localization, particularly multirobot localization, is an important task for multirobot teams. In this paper, a decentralized cooperative localization (DCL) algorithm with fault detection and isolation is proposed to estimate the positions of robots in mobile robot teams. To calculate the interestimate correlations in a distributed manner, the split covariance intersection filter (SCIF) is applied in the algorithm. Based on the split covariance intersection filter cooperative localization (SCIFCL) algorithm, we adopt fault detection and isolation (FDI) to improve the robustness and accuracy of the DCL results. In the proposed algorithm, the signature matrix of the original FDI algorithm is modified for application to DCL. A simulation-based comparative study is conducted to demonstrate the effectiveness of the proposed algorithm.

关键词

Fault detection and isolationCovariance intersectionRobustness (evolution)RobotIntersection (aeronautics)CovarianceComputer scienceIsolation (microbiology)Mobile robotFilter (signal processing)

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