Archive for the ‘Case Studies’ Category

Customer Story: Evolutionary Robotics Using NMath

Monday, October 14th, 2013

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).

Jaroslav says:

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


CEM Solver at UT Austin

Wednesday, November 2nd, 2011

The folks at the Center for Electromechanics at University of Texas at Austin (UT-CEM) are doing some neat simulation projects with power systems, and we were honored to learn that NMath is at the core of their CEM Solver software. CEM Solver demonstrates substantial performance improvements over SimPowerSystems, reducing simulation time for a typical example from 23 minutes down to 30 seconds, for a 46x improvement!

Dr. Fabian M. Uriarte, Research Associate at UT-CEM, recently had this to say about NMath:

“If performance, documentation, and reliable technical support are important to you, then NMath is what you need. In our application, we parallelize the solution of large, sparse Ax=b systems. Using NMath, we saw significant performance gains over Math.NET. Additionally, NMath has a very large set of classes that suit our needs in other numerical aspects as well. We are extremely pleased with the performance of NMath and highly recommend it to others. This library is a ‘must have.’"

Thanks for the kind words, Fabian!  You can check out the CEM Solver project at, or check out the demonstration video below.