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

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

No abstract

This paper discusses the forbidden state problem, as specified by generalized mutual exclusion constraints, in the context of supervisory control of discrete event systems modelled by Petri nets. The case of backward-conflict-free and free-choice uncontrollable subnets is considered and it is shown how to transform such subnets in well-formed free-choice nets. Then, the wellformed free-choice nets are decomposed in marked graph components by recurring to minimal T-invariants. The forbidden state problem is so reformulated for the obtained marked graph components into an equivalent one which is shown to be a linear programming problem. Thus, improving existing results in literature, a polynomial complexity solution, suitable for on-line control, is achieved. Free-choice relationship and cycle modelling, that frequently occur in real-life situations, are so allowed in the uncontrollable subnet.Index Terms-Backward conflict free net, free choice net, Petri nets, state feedback, supervisory control.

No abstract