Iterative MILP Methods for Vehicle Control Problems

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Mixed integer linear programming (MILP) is a powerful tool for planning and control problems because of its modeling capability and the availability of good solvers. However, for large models, MILP methods suffer computationally. In this paper, we present iterative MILP algorithms that address this issue. We consider trajectory generation problems with obstacle avoidance requirements and minimum time trajectory generation problems. The algorithms use fewer binary variables than standard MILP methods and require less computational effort.
22 pages, 9 figures, submitted to IEEE Transactions on Robotics, for associated web page see http://control.mae.cornell.edu/earl/milp2

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Robotics, I.2.9; I.2.8; J.2

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http://salesiana.dossiersoluciones.com/handle/123456789/96437

Consulte el texto completo en el siguiente enlace:

https://arxiv.org/abs/cs/0505042
 http://arxiv.org/abs/cs/0505042
 M. G. Earl and R. D'Andrea, "Iterative MILP Methods for Vehicle Control Problems," IEEE Transactions on Robotics, Volume 21, Issue 6, pages 1158-1167, Dec. 2005.

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arXiv