Lorenzo Pollini

Autonomous formation flight

This article describes an approach to close-formation flight of autonomous aircraft. A standard LQ-based structure was synthesized for each vehicle and for formation position error control using linearized equations of motion and a lifting line model of the aircraft wake. We also consider the definition of a formation management structure, capable of dealing with a variety of generic transmission and communication failures among aircraft. The procedure was developed using a decentralized approach and relies on the Dijkstra algorithm. The algorithm provides optimal path information sequencing in the nominal case, as well as the redundancy needed to accommodate failures in data transmission and reception. Several simulations were carried out, and some of the results are presented. The overall scheme appears to be a valuable starting point for further research, especially specialization to situations representing more detailed and operational failures.

A synthetic environment for dynamic systems control and distributed simulation

Rapid prototyping and controlled motion evaluation of complex human-machine interfaces, from nuclear plant operation panels to deep submerged underwater vehicles to advanced airplane cockpits, require hardware-in-the-loop, man-in-the-loop, and software integration. What appears to be needed is specific software to give designers tools for analyzing and simulating complex and integrated projects. The research software described in this article promises to fill that need, providing a new synthetic environment for simulation and control synthesis of dynamic systems. The article addresses problems of high performance, realistic environments, and vehicle simulation, with particular attention to synthetic world creation and visualization. The new software is capable of handling most of the simulation and visualization requirements highlighted.

Vision Algorithms for Formation Flight and Aerial Refueling with Optimal Marker Labeling

This pa per presents the experimental results of an artificial vision system prototype for application to unmanned formation flight and aerial refueling. In the former, a camera on the wingman captures leader images, estimating the relative position; in the latte r, using probe -and -drogue refueling, the aircraft camera acquires basket images, and from that estimating the relative position. Position estimation is based on localization of infrared markers which hav e a known geometry distribution over the leader airfr ame or drogue body . Experimental results using a low cost simulated formation flight setup are shown, to validate the procedure.

Simulation and Robust Backstepping Control of a Quadrotor Aircraft

This paper presents the development of a fully non-linear quadrotor aircraft simulator together with a non-linear control system design methodology which stabilizes the system and is robust to a class of measurement errors. The focus of this work is on design of a robust nonlinear Backstepping control system capable of handling some of the disturbances modeled in the simulator. The controller synthesis is performed into two steps: first a nominal controller is designed for attitude stabilization, then measurement disturbances are introduced in the design; as second step, the control laws are redesigned, so that, given bounds on the maximum absolute values of the measurement disturbances, the closed-loop system is robustly stable and the maximum absolute values of steady state tracking error fall within a desired bound. The new control laws are shown to Practically Asymptotically Stabilize the system, and to bring the tracking error inside an area of the state space of desired dimensions; furthermore, bounds on the control gains, which ensure convergence and stability, are derived. The new control laws were extensively tested with the simulator and yielded the desired bounds on the tracking error. An outer loop controller for position control was designed as well, in order to be able to test the overall system. Simulation results are presented.

Fast unmanned vehicles task allocation with moving targets

This paper presents a fast algorithm for allocation at mission-time of moving targets to a group of unmanned vehicles. A fleet of UAVs must fly through a known environment to reach partially unknown locations, or targets, where three tasks: identification, attack and verification must be performed sequentially. The total mission cost is identified to be the sum of the total times that the UAVs spend completing their tasks, while respecting the task priorities and ensuring the task precedence laws. The problem is solved in two steps; the first step is performed off-line and is the most computationally intensive: the environment is subdivided into triangle-shaped areas forming the tessellation graph (TG), and the shortest path between each two vertexes couples of the plane is computed using the all-pairs-nodes Dijkstra algorithm. The second step, at mission-time, regards management of moving targets and adaptation to the results of the identification phase. Optimal task assignment is performed using the Hungarian algorithm; exact path lengths between vehicles and targets are computed from the off-line computed Dijkstra paths. One parameter is available to tune the optimal task allocation algorithm with respect to desired aggressive/selfish or cooperative behavior.

Experimental Evaluation of Vision Algorithms for Formation Flight and Aerial Refueling

The development of an artificial vision system to be used in formation flight and aerial refueling is presented. In the former, a camera on the wingman captures leader images, estimating the relative position; in the latter, using probe-and-drogue refueling, the aircraft camera acquires basket images, and from that estimating the relative position. Position estimation is based on infrared markers localization, having a known geometry distribution. Experimental results using a low cost simulated formation flight setup are shown, to validate the procedure.

Robustness to communication failures within formation flight

Concerns formation flight of unmanned air vehicles. Presents the evolution and finite state machine implementation of a deterministic approach to the problem of management of communication faults and aircraft loss inside a formation in autonomous flight. The aircraft formation is represented as an oriented graph and then a procedure, based on the shortest path theory, provides the optimal solution for the information flow within the formation. In case of faults this procedure run again providing with a sub-optimal solution while the formation geometry is changed by a formation manager that uses reconfiguration maps and heuristic laws to find the new best placement for the aircraft in the formation. Theoretical development and simulation results validating the fault management methodology are presented. The next step is testing of this formation management structure on a formation of flying UAV.

A comparison of Direct and Indirect Haptic Aiding for Remotely Piloted Vehicles

The paper presents an experimental evaluation of two different Haptic aiding concepts: Direct and Indirect Haptic Aiding. Two Haptic systems were designed and tested using an experimental setup. The problem of wind gust rejection in Remotely Piloted Vehicles is used as test bench. Test results show the effectiveness of both methods but a better performance of the IHA-based system for pilots without any previous training about the experiment. DHA-based system provided instead better results after some pilot training on the experiment. Pilots reported better sensation of the wind gusts with IHA-based feedback.

Management of Communication Failures in Formation Flight

This paper addresses the problem of the management of unmanned air vehicles flying in formation, in the presence of failures in the communication system or aircraft loss. The problem is solved representing the formation as an oriented graph, and a procedure based on shortest path theory provides the optimal solution for the information flow within the formation. When a failure occurs, the procedure runs again providing a sub-optimal solution, and formation geometry is changed according to pre-set reconfiguration maps. Formal definitions, such as the novel definition of Virtual Leader, and simulation results validate the methodology.

A Fuzzy Approach to the Guidance of Unmanned Air Vehicles Tracking Moving Targets

This paper presents the development of a fuzzy guidance system for unmanned aircraft based on waypoints described in a 5-D space: position in 3-dimensions, desired crossing heading, and speed. The aircraft is assumed to be auto piloted in speed, heading, and flight path angle. The proposed system uses standard Takagi-Sugeno fuzzy controllers that provide speed, heading, and flight path angle references for the autopilots. In particular, the heading guidance law results in a pipeline of two fuzzy controllers depending on the relative distance between aircraft and waypoint. A trajectory optimization algorithm is used to yield a long-distance guidance law blended with a short-distance guidance law as the waypoint approaches. The system handles sets of not directly flyable waypoints, driving the aircraft on flyable trajectories that try to cross the waypoints at a prescribed altitude and heading.