Carmelo Donato Melita

An Overview of the Volcan Project: An UAS for Exploration of Volcanic Environments

This paper presents an overview of the Volcan Project, whose goal is the realization of an autonomous aerial system able to perform aerial surveillance of volcanic areas and to analyze the composition of gases inside volcanic plumes. There are increasing experimental evidences that measuring the chemical composition of volcanic gases can contribute to forecast volcanic eruptions. However, in situ gas sampling is a difficult operation and often exposes scientists to significant risks. At this aim, an Unmanned Aircraft System equipped with remote sensing technologies, able to sense the plume in the proximity of the crater, has been developed. In this paper, the aerial platform will be presented, together with the problems related to the flight in a hard scenario like the volcanic one and the tests performed with the aim of finding the right configuration for the vehicle. The developed autonomous navigation system and the sensors unit for gas analysis will be introduced; at the end, several experimental results will be described.

UAV/UGV cooperation for surveying operations in humanitarian demining

Unmanned Ground Vehicles can be a useful tool to help operators in humanitarian demining. However in many difficult environments autonomous operations are impossible and moreover it can be really difficult to teleoperate the robot from an onboard camera. This work presents an architecture to allow cooperation between a ground robot and a quadrotor UAV. The UAV can autonomously follow the ground robot, by using an image processing algorithm. In this way aerial images are provided that can help trajectory planning in rough environments, via a developed webGIS platform.

Volcanic Environments: Robots for Exploration and Measurement

The study of volcanic activity is important from a scientific point of view as it allows for a better understanding of one of the most spectacular geological phenomena and of the working principles that are at the basis of geophysics. Furthermore, there are numerous events that directly result from volcanic eruptions and that affect many populations. Therefore, improving the prediction methods of eruptive phenomena would be of great benefit. There are more than 1,500 potentially active volcanoes in the world, and roughly 10% of the worlds population live in areas directly threatened by volcanoes. In all of these areas, volcanoes have a strong influence on many day-to-day activities. The eruption of Eyjafjallajökull in Iceland in April 2010 caused the cancellation of more than 100,000 European flights and, consequently, left more than 10 million passengers stranded. Each year, on a graver note, many regions in the world are destroyed or heavily damaged by lava or pyroclastic flows, in some cases, resulting in numbers of casualties that could have been avoided with the improvement of early warning systems.

HIL Tuning of UAV for Exploration of Risky Environments

In this paper the latest results of an HIL architecture, optimized to develop and test UAV platforms are presented. This architecture has been used to realize the different devices involved in the navigation and stability control of the Volcan UAV, a plane designed to operate in volcanic environments. The proposed architecture is strongly modular and flexible and allows the development of avionic hardware and software, testing and tuning the involved algorithms with non-destructive trials. A flight simulator (X-Plane) with a suitable plane model and plug-in, has been adopted to simulate the UAV dynamics. The flight simulator, interfaced with the real electronic boards, allows an easy tuning of all the control parameters and data collecting for test and validation. The effectiveness of adopted methodology was confirmed by several flight tests performed subsequently by using the designed avionic modules on the real UAV.

Automatic Tuning Architecture for the Navigation Control Loops of Unmanned Aerial Vehicles

One of the most time consuming phases in the development of an Unmanned Aerial Vehicle is the tuning of the control algorithms. In this paper the hardware and software suite developed for the self-tuning of the control loops of unmanned flying platforms is presented. The VOLCAN UAV has been used as platform to test and validate the developed architecture. The simplified control system of the VOLCAN UAV is described, together with the Graphical User Interface that allows the rapid automatic tuning of the system by means of Åström and Hägglund’s method. The Hardware in the Loop architecture used to test both the control algorithms and the tuning procedure is presented in the final part of the paper, together with the obtained experimental results.

An architecture for automatic tuning of the navigation system of Unmanned Aerial Vehicles

In this paper the architecture developed for the automatic tuning of the control loops of Unmanned Aerial Vehicles is presented. In order to validate this architecture, the VOLCAN UAV has been used as test platform. The simplified control system of the VOLCAN UAV, based on cascade controls of PIDs, is introduced, together with the automatic procedure that has been implemented. A Human Machine Interface allows the rapid automatic tuning of the system by means of Åström and Hägglunds method. Finally, the Hardware in the Loop architecture used to test both the control algorithms and the tuning procedure is presented.

A Simulation Environment for an Augmented Global Navigation Satellite System Assisted Autonomous Robotic Lawn-Mower

This paper presents the software architecture that was developed to evaluate the performance of different Global Navigation Satellite Systems (GNSSs) and Satellite/Ground-Based Augmentation Systems for the localization and navigation of an autonomous robotic lawn-mower. In particular, a complete simulation environment has been developed to analyse the system performance obtained by adopting the future European GNSSs when GALILEO will be fully operative. Moreover, this tool has been adopted in the development phase of a precise GNSS-based localization system and developed within the MOW-BY-SAT project, an FP7 project funded by the European Commission; this architecture relies on an innovative algorithm that allows for a Real Time Kinematic localization system, while requiring only a pair of low-cost GPS receivers. The results show the validity of the developed localization and control architecture and the potential of the future European GALILEO system.

3D path planning for UAV swarm missions

In this paper, a strategy for the mission planning of a UAV swarm in 3-D environments is presented. The operating space is represented as a 3-D grid and the A* algorithm is used; paths are planned for each UAV towards any possible target and the optimal combination, in terms of reducing the path length for the whole swarm, is considered. Further features and algorithm enhancements have been developed for reducing computational time, improving planned trajectories, and for the automatic redistribution of targets. The intended application is the deployment of UAVs for landslide monitoring and search of people involved in catastrophic events.

A System for Autonomous Landing of a UAV on a Moving Vehicle

This paper describes the approach employed to implement the autonomous landing of an Unmanned Aerial Vehicle (UAV) upon a moving ground vehicle. We consider an application scenario in which a target, made of a visual pattern, is mounted on the top of a ground vehicle which roams in an arena using a certain path and velocity; the UAV is asked to find the ground vehicle, by detecting the visual pattern, and then to track it in order to perform the approach and finalize the landing. To this aim, Computer Vision is adopted to perform both detection and tracking of the visual target; the algorithm used is based on the TLD (Tracking-Learning-Detection) approach, suitably integrated with an Hough Transform able to improve the precision of the identification of the 3D coordinates of the pattern. The output of the Computer Vision algorithm is then exploited by a Kalman filter which performs the estimation of the trajectory of the ground vehicle in order to let the UAV track, follow and approach it. The paper describes the software and hardware architecture of the overall application running on the UAV. The application described has been practically used with success in the context of the “Mohamed Bin Zayed” International Robotic Challenge (MBZIRC) which took place in March 2017 in Abu Dhabi.