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Data association is a fundamental problem in multisensor fusion, tracking, and localization. The joint compatibility test is commonly regarded as the true solution to the problem. However, traditional joint compatibility tests are computationally expensive, are sensitive to linearization errors, and require the knowledge of the full covariance matrix of state variables. The paper proposes a posterior-based...
One of the fundamental challenges in robotics is data-association: determining which sensor observations correspond to the same physical object. A common approach is to consider groups of observations simultaneously: a constellation of observations can be significantly less ambiguous than the observations considered individually. The Joint Compatibility Branch and Bound (JCBB) test is the gold standard...
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