The objective of this work is to develop, implement, and test robust decentralized strategies for path-following control and time-coordination of a fleet of multiple autonomous vehicles supported by an inter-vehicle dynamic communications network.

Conceptual architecture of the cooperative control framework adopted.

The methodology for time-critical cooperative path-following control developed at the ACRL (in collaboration with NPS and IST) can be summarized in three basic steps:

  1. Initially, each vehicle is assigned a feasible path with a desired speed profile that together satisfy the mission requirements and the vehicle dynamic constraints, while ensuring collision-free maneuvers.
  2. Then, a path-following algorithm ensures that every vehicle follows its own path independently of the temporal assignments of the mission.
  3. Finally, the vehicles coordinate their position along the path with the remaining vehicles engaged in the mission by exchanging coordination information over the supporting communications network.

These three steps are accomplished by judiciously decoupling space and time in the formulation of the trajectory-generation, path-following, and time-coordination problems. Moreover, the approach adopted applies to teams of heterogeneous vehicles and does not necessarily lead to swarming behavior, which is unsuitable for many of the mission scenarios envisioned in this project.

The control algorithn has been implemented on Fixed Wing and Quadrotor UAVs

  1. Xargay, Dobrokhodov, Kaminer, Pascoal, Hovakimyan, and Cao, “Time-Critical Cooperative Control for Multiple Autonomous Vehicles,” to appear in IEEE Control Systems Magazine, 2012.
  2. Xargay, Kaminer, Pascoal, Hovakimyan, Dobrokhodov, Cichella, Aguiar, and Ghabcheloo, “Time-Critical Cooperative Path Following of Multiple UAVs over Time-Varying Networks,” submitted to Journal of Guidance, Control, and Dynamics, 2011.
  3. V. Cichella, I. Kaminer, E. Xargay, V. Dobrokhodov, N. Hovakimyan, P. Aguiar, and A. Pascoal, “A Lyapunov-based approach for Time-Coordinated 3D Path-Following of multiple Quadrotors in SO(3),” accepted for publication, Conference on Decision and Control, December 2012.


    Naira Hovakimyan
    Enric Xargay
    Vladimir Dobrokhodov
    Isaac Kaminer
    nhovakim (at) illinois (dot) edu
    xargay (at) illinois (dot) edu
    vldobr (at) nps (dot) edu
    kaminer (at) nps (dot) edu