Abstract
Decades of advances in electronics and communication technologies have enabled large-scale, flexible, reconfigurable multiple-UAV systems with a variety of applications ranging from large-scale military surveillance and reconnaissance to environmental monitoring and disaster response. Most of these applications require multiple tasks and service requests to be handled by a large group of UAVs in an efficient manner. Motivated by these problems, this chapter is devoted to a large-scale distributed task/target assignment problem for a fleet of autonomous UAVs. Central to this chapter is an algorithm that uses the delayed column generation approach on a non-convex supply-demand formulation for the problem. The algorithm exploits a computationally tractable distributed coordination structure, i.e., a market for tasks and targets created by the UAV fleet. The resulting structure is solved via a fleet-optimal dual simplex ascent in which each UAV updates its respective flight plan costs with a linear update of waypoint task values as evaluated by the market. Synchronized and asynchronous distributed implementations of this approximation algorithm is demonstrated in a thorough experimental study involving dynamically changing scenarios with random pop-up targets. Results from the tests performed on an in-house built network mission simulator are also provided for the numerical verification of the algorithm on (a) bounded polynomial-time computational complexity and (b) hard real-time performance for problem sizes on the order of 100 waypoints per UAV.
Original language | English |
---|---|
Title of host publication | Handbook of Unmanned Aerial Vehicles |
Publisher | Springer Netherlands |
Pages | 1601-1617 |
Number of pages | 17 |
ISBN (Electronic) | 9789048197071 |
ISBN (Print) | 2014944662, 9789048197064 |
DOIs | |
Publication status | Published - 1 Jan 2015 |
Bibliographical note
Publisher Copyright:© Springer Science+Business Media Dordrecht 2015.