Real-time optimal time-critical target assignment for UAVs

Kim, Yoonsoo, Gu, Da-Wei and Postlethwaite, Ian (2007) Real-time optimal time-critical target assignment for UAVs. In: Advances in Cooperative Control and Optimization. Lecture Notes in Control and Information Sciences, 369 . Springer, London, pp. 265-280. ISBN 978-3540743545

Full text not available from this repository. (Request a copy)
Official URL: http://dx.doi.org/10.1007/978-3-540-74356-9_16

Abstract

In the literature, e.g. [10], one can find the so-called basic UAV mission target assignment in which m UAVs each with a capacity limit q visit n targets in a cooperative manner (and return to their departure points) such that the cost incurred by each UAV’s travel is minimized. In [10], we proposed a mixed integer linear program (MILP) formulation which exactly solves the problem, as well as four alternative MILP formulations which are computationally less intensive (and therefore suited for real-time purposes) yet yield a theoretically guaranteed sub-optimal solution. In this chapter, we further consider timing constraints imposed on some p of the targets, so-called prime targets. This consideration is often required for scenarios in which prime targets must be visited in a pre-defined time interval, and mathematically results in the addition of several integer linear constraints to the previous MILP formulation making the problem computationally intractable. We propose a novel procedure of adding these cumbersome timing constraints to the previous MILP formulation, in order to avoid increasing too much computational cost under practically valid assumptions. We first show that the proposed procedure still guarantees the previously claimed theoretical solution quality associated with the basic mission. We then show through extensive numerical simulations that under certain conditions, our algorithms return solutions which are still computationally manageable.

Item Type: Book Section
Subjects: G900 Others in Mathematical and Computing Sciences
H600 Electronic and Electrical Engineering
Department: Faculties > Engineering and Environment > Mathematics, Physics and Electrical Engineering
Depositing User: Sarah Howells
Date Deposited: 21 Nov 2012 14:04
Last Modified: 12 Oct 2019 22:26
URI: http://nrl.northumbria.ac.uk/id/eprint/10344

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics