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bneveu/tubex-v3

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Tubex is a library providing tools for constraint programming over reals and trajectories. It has many applications in state estimation or robot localization.

| What is constraint programming? | In this paradigm, users concentrate on the properties of a solution to be found (e.g. the pose of a robot, the location of a landmark) by stating constraints on the variables. Then, a solver performs constraint propagation on the variables and provides a reliable set of feasible solutions corresponding to the considered problem. In this approach, the user concentrates on what is the problem instead of how to solve it, thus leaving the computer dealing with the how. The strength of this declarative paradigm lies in its simpleness, as it allows one to describe a complex problem without requiring the knowledge of resolution tools coming with specific parameters to choose.

| What about mobile robotics? | In the field of robotics, complex problems such as non-linear state estimation, delays, SLAM or kidnapped robot problems can be solved in a very few steps by using constraint programming. Even though the Tubex library is not meant to target only robotics problems, the design of its interface has been largely influenced by the needs of the above class of applications. Tubex provides solutions to deal with these problems, that are usually hardly solvable by conventional methods such as particle approaches or Kalman filters.

In a nutshell, Tubex is a high-level constraint programming framework providing tools to easily solve a wide range of robotic problems.

See the official page.

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This software is under GNU Lesser General Public License.

A Python version (pyIbex wrapping) is planned.

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