This paper presents a fully autonomous multisensor anti-collision system for Unmanned Aerial Vehicles (UAVs). This system is being developed by the Italian Aerospace Research Center (CIRA) in collaboration with the Dept. of Aerospace Engineering of the University of Naples “Federico II”, within a research project named TECVOL, funded in the frame of the National Aerospace Research Program (PRO.R.A.) on UAV. The system prototype will be initially installed onboard a manned laboratory aircraft equipped for automatic control so that flight tests will verify the adequacy of attained performances for supporting fully autonomous flight. In order to perform the obstacle detection and identification function, a multisensor configuration has been designed in the TECVOL preliminary studies. The hardware configuration is made up by a pulsed Ka-band radar, two visible (panchromatic and colour) videocameras, two infrared (IR) videocameras, and two computers, one dedicated to sensor fusion and communication with the flight control computer and with the radar, the other devoted to image processing. They are connected to the Flight Control Computer by means of a deterministic data bus. On the basis of these tracking estimates and of a Collision Avoidance Software, the GNC computer generates and follows in real time a proper escape trajectory. In order to evaluate the performance of the entire collision avoidance system, numerical simulations have been performed taking into account the DS&A sensors’ accuracy, UAV’s and intruder’s flight dynamics, navigation system accuracy and latencies, collision avoidance logic, and practical real-time implementation issues. The relevant results helped to assess overall system performances. They are discussed in depth at the end of the paper

In this brief, we consider the problem of 3-D path generation and tracking for unmanned air vehicles (UAVs). The proposed path generation algorithm allows us to find a path satisfying arbitrary initial and final conditions, specified in terms of position and velocity. Our method assumes that aircraft structural and dynamic limitations can be translated in a turn radius constraint; therefore, the generated paths satisfy a constraint on the minimum admissible turning radius. The proposed algorithm for the path tracking guarantees, under specified assumptions, that the tracking error, both in position and in attitude, asymptotically tends to zero. The work has been carried out with reference to the UAV of the Italian Aerospace Research Center (CIRA). Simulation results for both the path generation and the tracking algorithms are presented; the latter have been obtained using a detailed 6-degree-of-freedom model of the CIRA UAV in the presence of wind and turbulence.

This paper presents a novel decision-making algorithm for pair wise non-cooperative aircraft mid-air collision avoidance. An analytical solution for this control problem, based on a three dimensional geometric approach, is derived. It does not require the solution of any programming problem, thus resulting suitable for real-time applications. Moreover, the availability of an analytical solution allows the application of well assessed control analysis and synthesis techniques in order to improve stability and performance robustness. The proposed algorithm performs optimal avoidance maneuvers, both in the horizontal and vertical plane, by minimizing aircraft deviation from its nominal trajectory. Its effectiveness has been proved via numerical simulations, in proper conflict scenarios which take into account aircraft dynamics and on-board sensors limitations.I. INTRODUCTION AIRCRAFT mid-air collision is still an unresolved problem, as available mishap data [1] show. This situation is anticipated to become worse with the increasing emerging traffic of small business aircraft, Very Light Aircraft (VLA) operating from and to secondary airports. On the other hand, in order to increase aircraft capacity in the airspace, with the expected increase of civil Unmanned Aircraft Vehicles (UAVs) a robust autonomous collision avoidance (ACA) system must be designed, developed and put in place [3]. Notice that an ACA system works on a short-term time horizon (less than one minute) and it is considered as an emergency function autonomously engaged, at close ranges [2].In general, it is composed of on-board detection sensors and decision-making algorithms. This paper focuses only on the decision-making algorithm part.A comprehensive survey of conflict detection and resolution approaches is provided in [4]. It is worthwhile noticing that most of the methods presented in literature are not suitable for real-time applications, because of the nondeterministic computational time needed for taking a decision. In [5] authors solve the problem of two aircraft conflict-prone as a two-person zero-sum dynamic game of the pursuer-evader variety, by computing reachable sets defining regions of guaranteed safety. The main disadvantage of this approach is that the algorithm takes

In this paper we consider the problem of 3D path generation and tracking for unmanned air vehicles (UAVs). The proposed path generation algorithm allows us to find a path satisfying arbitrary initial and final conditions, specified in terms of position and velocity. Our method assumes that most of aircraft structural and dynamic limitations can be translated in a turn radius constraint; therefore, the generated paths satisfy a constraint on the minimum admissible turning radius. The proposed algorithm for the path tracking guarantees, under specified assumptions, that the tracking error, both in position and in attitude, asymptotically tends to zero. The work has been carried out with reference to the UAV of the Italian Aerospace Research Center (CIRA). Simulation results for both the path generation and the tracking algorithms are presented; the latter have been obtained using a detailed 6-degree-of-freedom model of the CIRA UAV in the presence of wind and turbulence.

This paper presents an innovative 3D analytical algorithm for the resolution of the pair-wise noncooperative collision avoidance problem between aircrafts. The proposed algorithm addresses the above described problem by using an innovative approach, based on the consideration of a cylindrical safety bubble, and it is able to obtain an optimal three-dimensional analytical solution for this problem. This novel approach allows different minimum separations on the vertical and horizontal planes with respect to the nominal trajectory to be achieved, so minimizing the impact of the collision avoidance maneuver on surrounding traffic. Moreover, the algorithm has the very interesting feature that it does not require the solution of any non deterministic and/or iterative problem, resulting suitable for real-time applications. This is due to the capability of the algorithm to find a closed form solution for the kinematic optimization problem here considered. The solution of the collision avoidance problem requires the simultaneous change of all control variables (speed module, track and slope angles), aiming to assure the required safety level and, at the same time, to minimize aircraft deviation from the nominal trajectory. This system is mainly developed for unmanned aircraft vehicles, where high levels of autonomy (i.e. the avoidance maneuver is autonomously executed by a standard autopilot) are required, but it can also be used, as aid to pilots, in manned commercial aircrafts. The effectiveness of the algorithm is evaluated by means of numerical simulations, where suitable conflict scenarios, taking into account aircraft dynamics and on-board sensors errors and limitations, are considered. Scenarios where both aircrafts are equipped with the proposed collision avoidance algorithm or where both aircrafts are subjected to Visual Flight Rules are also considered. 1 2