Autonomous underwater vehicles have proven their roles as useful tools for scientific exploration and data gathering. The current state of the art in commercial vehicles involves a statical mission planning phase which does not take into account any energy or time limits. This work proposes the use of a mixed integer quadratic programming solution that maximises the utility of data gathering missions under time or energy constraints. This method is compared against other constrained and unconstrained mixed integer linear programming methods. Results confirm that the method is producing better quality paths in the expense of higher computation time.
|Title of host publication||OCEANS 2016 - Shanghai|
|Publication status||Published - 9 Jun 2016|
|Event||OCEANS 2016 - Shanghhai, China|
Duration: 10 Apr 2016 → 13 Apr 2016
|Period||10/04/16 → 13/04/16|
ASJC Scopus subject areas
- Automotive Engineering