The paper presents a multi-hypothesis filter library featuring a novel method for splitting Gaussians into ones with smaller variances. The library is written in C++ for high performance and the source code is open and free1. The multi-hypothesis filters commonly approximate the distribution transformations better, if the covariances of the individual hypotheses are sufficiently small. We propose a look-up table based method to calculate a set of Gaussian hypotheses approximating a wider Gaussian in order to improve the filter approximation. Python bindings for the library are also provided for fast prototyping.
Proceedings of the 2013 10th Ieee International Conference on Control and Automation, 2013, p. 574-579
Approximation theory; C++ language; Filtering theory; Gaussian distribution; Mobile robots; Public domain software; Software libraries; Table lookup
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2013 10th IEEE International Conference on Control and Automation (ICCA), 2013