This paper implements several methods for performing vision-based formation flight control of multiple aircraft in the presence of obstacles. No information is communicated between aircraft, and only passive 2-D vision information is available to maintain formation. The methods for formation control rely either on estimating the range from 2-D vision information by using Extended Kalman Filters or directly regulating the size of the image subtended by a leader aircraft on the image plane. When the image size is not a reliable measurement, especially at large ranges, we consider the use of bearing-only information. In this case, observability with respect to the relative distance between vehicles is accomplished by the design of a time-dependent formation geometry. To improve the robustness of the estimation process with respect to unknown leader aircraft acceleration, we augment the EKF with an adaptive neural network. 2-D and 3-D simulation results are presented that illustrate the various approaches.

In considering the problem of formation control in the deployment of intelligent munitions, it would be highly desirable, both from a mission and a cost perspective, to limit the information that is transmitted between vehicles in formation. However, the lack of information regarding the state of motion of neighboring vehicles can lead to degraded performance and even instability. This paper presents an adaptive output feedback approach for addressing this problem. We design adaptive formation controllers that allow each vehicle in formation to maintain separation and relative orientation with respect to neighboring vehicles, while avoiding obstacles. The method works by enabling each vehicle in the formation to adaptively correct for the effect that the motions of neighboring vehicles have when regulating relative variables like range and line of sight. It is assumed that estimates of these variables can be derived using passive, vision-based sensors. The need for explicit communication to maintain formation is minimized and the resulting controller solution is decentralized. We implement a reactive obstacle avoidance controller to navigate in an environment with obstacles. The formation controller and obstacle avoidance controller are outer-loop controllers whose outputs are speed and heading commands. These commands are blended together to generate composite speed and heading commands that are inputs to the inner-loop controller. The weights used for blending the commands depend upon the priority of the task at hand. We illustrate the method with an example involving a team of three aircraft keeping formation in the presence of obstacles.

This paper presents an integrated guidance and control design for formation flight using a combination of adaptive output feedback and backstepping techniques without an underlying timescale separation assumption. We formulate the problem as an adaptive output feedback control problem for a line-of-sight (LOS) based formation flight configuration of a leader and a follower aircraft. The design objective is to regulate range and two bearing angle rates while maintaining turn coordination. Adaptive neural networks are trained online with available measurements to compensate for unmodeled nonlinearities in the design process. These include uncertainties due to unknown leader aircraft acceleration, and the modeling error due to parametric uncertainties in the aircraft aerodynamic derivatives. One benefit of this approach is that the guidance and flight control design process is integrated. Simulation results using a nonlinear 6DOF simulation model are presented to illustrate the efficacy of the approach by comparing the performance with a timescale separation based design.

In considering the problem of formation control in the deployment of intelligent munitions, it would be highly desirable, both from a mission and a cost perspective, to limit the information that is transmitted between vehicles in formation. In a previous paper, we proposed an adaptive output feedback approach to address this problem. Adaptive formation controllers were designed that allow each vehicle in formation to maintain separation and relative orientation with respect to neighboring vehicles, while avoiding obstacles. In this paper, we consider a modification to the adaptive control law that enables each vehicle in a leader-follower formation to track line-of-sight (LOS) range with respect to two or more neighboring vehicles with zero steady-state error. We also propose a coordination scheme in which each vehicle tracks LOS range to up to two nearest vehicles while simultaneously navigating towards a common set of waypoints. This coordination scheme does not require a unique leader for the formation, increasing robustness of the formation. As our results show, such leaderless formations can perform maneuvers like splitting to go around obstacles, rejoining after negotiating the obstacles, and changing into line-shaped formation in order to move through narrow corridors. I.

No abstract