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Solving Non-linear Arithmetic Constraints in Soft Realtime Environments

. Proceedings of the 27th Annual ACM Symposium on Applied Computing, page 67--73. New York, NY, USA, ACM, (2012)
DOI: 10.1145/2245276.2245293

Abstract

In many domains, such as in multi-robot scenarios, operational instructions controlling a system are highly complex. In order to facilitate both ease of modeling and intelligent decision making, powerful reasoning techniques become available, which are able to solve complex non-linear formulae within a very small time frame. We argue that the problem class of arbitrary boolean combinations of non-linear constraints is a suitable representation for a wide range of robotic problems and present an evaluation of several state-of-the-art solving techniques, targeting problems that arise in robotic and multi-robotic domains, which need to be solved in near real-time. Additionally, we combine available techniques yielding two highly competitive solvers for non-linear continuous constraint systems. Finally, we present new results on complexity phase transition phenomena of the local searches involved.

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