## Cooperative Path Planning for Multiple UAVs in Dynamic and Uncertain
Environments

### John S. Bellingham, Michael Tillerson, Mehdi Alighanbari and Jonathan
P. How

Proceedings of the IEEE Conference on Decision and Control, Las Vegas,
NV, Dec. 2002.

This paper addresses the problem of cooperative path
planning for a fleet of UAVs. The paths are optimized to account for uncertainty/adversaries
in the environment by modeling the probability of UAV loss. The approach
extends prior work by coupling the failure probabilities for each UAV to
the selected missions for all other UAVs. In order to maximize the expected
mission score, this stochastic formulation designs coordination plans that
optimally exploit the coupling effects of cooperation between UAVs to improve
survival probabilities. This allocation is shown to recover real-world
air operations planning strategies, and to provide significant improvements
over approaches that do not correctly account for UAV attrition. The algorithm
is implemented in an approximate decomposition approach that uses straight-line
paths to estimate the time-of-flight and risk for each mission. The
task allocation for the UAVs is then posed as a mixed-integer linear program
(MILP) that can be solved using CPLEX.

Download: Full Paper

Professor
Jonathan P. How

jhow@mit.edu

Mehdi Alighanbari

Jan. 31, 2003