Multi-Objective Coordinated Path Planning for a Team of UAVs in a Dynamic Environment
Abstract
UAVs are becoming ubiquitous due to their high-risk mission acceptance and ultra-long endurance capabilities. However, because a significant subset of UAVs have limited payload capacity and sensor ranges, teams of UAVs are often required to operate cooperatively in executing specific tasks (e.g., time-critical complex surveillance tasks requiring multiple UAVs) to ensure superior mission performance. In this paper, we model a coordinated path planning problem for a team of UAVs within a dynamic mission scenario that requires them to cooperatively execute time-critical mission tasks in the presence of manned aircraft. The problem is formulated as a multi-objective optimization problem and, more specifically, as a Mixed Integer Linear Programming problem. A major contribution of this paper lies in coordinating multiple UAVs to synchronize their arrival at locations requiring cooperative execution of mission tasks, while allowing for loitering en-route to avoid collisions and for maintaining a safe separation distance from manned aircraft or other obstacles. We solve this problem via a two-phase process. In phase I, we determine the path for each UAV by minimizing the cumulative mission risk; in phase II, we determine the arrival time of each UAV at every task location by following the path generated in phase I that minimizes the task latency to meet the specified deadlines.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jun 01, 2014
- Accession Number
- ADA606755
Entities
People
- David Lee Kleinman
- David Sidoti
- Diego Fernando MartÃnez Ayala
- Krishna R. Pattipati
- Manisha Mishra
- Woosun An
- Xu Han
Organizations
- University of Connecticut