Roberto Mati

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.

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.

Vision-Based Autonomous Probe and Drogue Aerial Refueling

This paper presents a simulation setup for probe and drogue autonomous aerial refueling. The overall system consists of tanker and UAV models, the hose model, the atmospheric disturbances and the formation keeping controllers and of a robust artificial vision system. The UAV model is a YF-22 developed at West Virginia University. The vision system is employed to allow the UAV to measure its relative displacement from the drogue with no radio communication between the two aircrafts. Simulation results show the performances of the entire system, with a main focus on the vision system

Stereo Vision Obstacle Detection based on Scale Invariant Feature Transform Algorithm

[Abstract] This paper presents a novel real-time obstacle detection system based on stereoscopic vision. The system was designed for an Unmanned Ground Vehicle (UGV) operating in an unstructured environment. The system is based on the Scale Invariant Feature Transform (SIFT) Algorithm. It permits to detect, track and reference obstacles with respect to a fixed inertial reference system. Experimental results are shown to demonstrate the validity of the approach.

Obstacle Avoidance for Unmanned Ground Vehicles in Unstructured Environments

[Abstract] The paper presents an obstacle avoidance algorithm to be used for Unmanned Ground Vehicles applications. The algorithm improves, and extends the recently developed Null Space Based Behavioral Control technique. The method divides the problem into various tasks with increasing priority. Activities with lower priority do not interfere with those having higher priority. The scenario is assumed only partially known, and the complete environment is reconstructed during the mission, with the aid of stereoscopic vision sensors. The validity of the method is verified first via computer simulations, and then by performing field experimentation. BSTACLE avoidance is one of the more complex problems to be addressed within the context of autonomous vehicles guidance design. Difficulties increase if the initial knowledge of the scenario is limited, and the outside environment must be reconstructed online, during the motion of the vehicle, and without a priori information and/or cues. The literature offers a large number of methods for the solution of the obstacle avoidance problem, and several of them use modifications of the potential algorithm adapted to represent vehicle trajectories and paths. Potentialbased techniques have the advantage of being straightforward and of easy implementation. One of the limitations encountered by these methods is the presence of local minima, which can be addressed in several ways, for instance by using harmonic functions 1 . In addition, the complexity of the scenarios is limited under the application of this

Obstacle Avoidance for Autonomous Ground Vehicles in Outdoor Environments

The paper presents an obstacle avoidance algorithm to be used for autonomous ground vehicles applications. The proposed method improves some of the limitations of the recently developed null space based behavioral control. The technique divides the problem into tasks, which are associated to increasing priority. Activities with lower priority do not interfere with those having higher priority. The scenario is supposed known only partially, and the complete environment is reconstructed during the mission, with the aid of stereoscopic vision sensors. The validity of the method is currently verified via computer simulations.

Design of an All-Electric Propulsion System and Control Management for a General Aviation Aircraft

The paper presents a preliminary design structure of an electric propulsion system and associated control management unit for a small twin-seater aircraft. This is part of a larger research project that involves design, simulation, and flight test of a piloted vehicle equipped with a single engine powered by a combination of fuel cells and batteries. The innovative aspects of this applied research project, make it the first full European effort to all-electric propelled air vehicle.