By Topic

Route Planning for Unmanned Air Vehicles with Multiple Missions Using an Evolutionary Algorithm

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Ruoding Zhang ; Chinese Academy of Sciences, China ; Changwen Zheng ; Ping Yan

In this paper, the route-planning problem for unmanned air vehicles with multiple missions is studied with the proposal of a novel evolutionary route planner. In the new planner, the individual candidates are evaluated with respect to the workspace. Therefore the computation of the configuration space is avoided. With digital terrain elevation data, our approach can find a near-optimal route that can increase the surviving probability efficiently. By using a problem-specific representation of candidate solutions and genetic operators, our algorithm can take into account different kinds of mission constraints and generate the solutions in real-time.

Published in:

Third International Conference on Natural Computation (ICNC 2007)  (Volume:3 )

Date of Conference:

24-27 Aug. 2007