We recently heard from NMath user Jaroslav Moravec of the Czech Technical University in Prague, the author of RobomapStudio, a smart tool designed to process data in the field of autonomous robotics and artificial intelligence. The program consists of more than 50 components for solving problems such as continual robot localization, global robot localization, and Simultaneous Localization and Mapping (SLAM).
I use NMath in RobomapStudio for evolutionary computations and robot pose estimation for navigation in known and partially known environments using 2D laser data. My Covariance Matrix Adaptation Evolution Strategy (CMAES) implementation is completely built on NMath. I also use NMath in a variety of other ways–for example, for various types of statistical distribution generating (Cauchy, Gauss etc.). NMath provides significantly better results (accuracy) and stability in comparison to the Iridium (Math.NET) library, for example. NMath is a great tool to solve, simply and easily, many numerical problems in MS VS C++/CLI .NET language.
RobomapStudio is part of the international OpenSLAM project of the University of Freiburg. Results of the RobomapStudio are used in several research groups at the Czech Technical University in Prague (for example, here and here), and by many other research centers around the world.
For more information on Jaroslav’s work using NMath, see his recent publication in the journal Evolutionary Intelligence (Sept. 2013).
How are you using NMath? We’re always interested in hearing about interesting applications of NMath “in the wild,” and in receiving suggestions for how NMath can be improved. Let us know at firstname.lastname@example.org.