Iterative MILP Methods for Vehicle Control Problems
<|reference_start|>Iterative MILP Methods for Vehicle Control Problems: 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.<|reference_end|>
@article{earl2005iterative,
    title={Iterative MILP Methods for Vehicle Control Problems},
    author={Matthew Earl and Raffaello D'Andrea},
    journal={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.},
    year={2005},
    archivePrefix={arXiv},
    eprint={cs/0505042},
    primaryClass={cs.RO}
}