Abstract
The effect of approximation has been well studied in stand-alone systems. However, the problem of approximation in a collaborative system has not been studied, to the best of our knowledge. The basic goal of this article is to study the applicability of approximation in collaborative SLAM (simultaneous localization and mapping). Our experiments suggest that it is not trivial to combine multiple stand-alone approximate results to achieve a collaborative approximation, i.e., the resultant error can not be bounded without special effort. Thus, we present a model of the problem and empirically show that such a model can be used to explain the error variance in a collaborative system.
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