Robust Loop Closure Selection Based on Inter-Robot and Intra-Robot Consistency for Multi-Robot Map Fusion
نویسندگان
چکیده
In multi-robot simultaneous localization and mapping (SLAM) systems, the system must create a consistent global map with multiple local maps loop closures between robot poses. However, false-positive caused by perceptual aliasing can severely distort map, especially in GNSS-denied areas, where good prior of relative poses robots is unavailable. addition, performance consistency metric existing fusion methods relies on accurate odometry from each robot. practice, cumulative noise inevitably present trajectories, which leads to poor methods. Thus, this paper, we propose robust consistency-based inter-robot intra-robot closure selection algorithm for fusion. We consider both pairwise-loop loop-odometry improve robustness against accumulative odometry. Specifically, select reliable measurement strategy provide an initial pose two trajectories update variables trajectories. The problem formulated as maximum edge weight clique graph theory. A evaluation proposed method was conducted ManhattanOlson3500, modified CSAIL Bicocca datasets, experimental results demonstrate that outperforms pairwise set maximization (PCM) under severe be integrated M-estimation
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ژورنال
عنوان ژورنال: Remote Sensing
سال: 2023
ISSN: ['2315-4632', '2315-4675']
DOI: https://doi.org/10.3390/rs15112796