Title :
Robust planning for coupled cooperative UAV missions
Author :
Bertuccelli, L.F. ; Alighanbari, M. ; How, J.P.
Author_Institution :
Aerosp. Controls Lab., MIT, MA, USA
Abstract :
This paper presents a new formulation for the UAV task assignment problem with uncertainty in the environment. The problem is posed as a task assignment with uncertainty in the cost information, and we apply a modified robust technique that allows the operator to tune the level of robustness in the optimization. This formulation is then used to solve the assignment problem for a heterogeneous fleet of vehicles operating in an uncertain environment. The key aspect of this formulation is that it directly addresses the inherent coupling in deciding how to assign vehicles to perform reconnaissance tasks that provide the most benefit to the strike part of the missions. We demonstrate that the robust solution to this coupled problem can be solved as single mixed-integer linear problem. The paper presents and discusses simulations for the proposed formulation, demonstrating significant improvements over previous ones.
Keywords :
aerospace robotics; integer programming; linear programming; mobile robots; multi-robot systems; planning (artificial intelligence); remotely operated vehicles; assignment problem; autonomous high-level planning capabilities; coupled cooperative UAV missions; mixed-integer linear problem; reconnaissance tasks; robust planning; uncertain environment; Aerospace control; Cost function; Finance; Operations research; Optimization methods; Reconnaissance; Robustness; Uncertainty; Unmanned aerial vehicles; Working environment noise;
Conference_Titel :
Decision and Control, 2004. CDC. 43rd IEEE Conference on
Print_ISBN :
0-7803-8682-5
DOI :
10.1109/CDC.2004.1428909