Paolo BOSETTI (Principal Investigator)

Francesco BIRAL 


Umberto IZZO

David MACII 






Requirement and specifications for both the drone and the testing facility are defined and collected, also according to the Quality Function Deployment approach. During this phase, the Advisory Board and the Alpine Rescue Service of the Autonomous Province of Trento are involved in defining requirements and use-case scenarios. Particular care is paid in defining the power and payload weight budget for the drone, taking into consideration statistics on survival time expectancy for buried people and number of buried people per avalanche. Also, a set of reference tests to be performed when assessing the prototype effectiveness is here defined.

Results: A Req&Spec manual is released after month 2, and later on it is updated when needed.

Members of the research team in this task: ALL.

  1. Drone Architecture

According to Task 1 outcome, this task carries out the design and development of the VTOL drone. Whenever possible and meaningful, off-the-shelf subsystems and components will be adopted, in order to minimize the development time. Prototyping facilities of the Mechatronics Group (Bosetti and Biral) as well as expertise in developing composite structures (Migliaresi) are exploited for realizing custom components and structures. Also, aerodynamics modeling and simulation expertise is available within the DII (Trivellato)

It is also investigated—and possibly implemented—the separation of some computational demanding, (but non time-critical) operations, which can be offloaded to a ground station (as the laptop/tablet controller) in order to limit the weight and power consumption of the drone.

A critical point is the definition of a hardware software architecture that permits an easy integration of hardware and software components. We will adopt a layered approach, with a bottom layer composed of low-power hardware (e.g., PIC or Arduino microcontrollers) used to control sensors and actuators and interconnected by a reliable bus infrastructure (e.g., CAN), and a top layer embedding all the computing hardware required for the processing of visual data, and for planning and control functions (which could be based on a quad-core ARM board). The software layer will build on top of an infrastructure consisting of a real-time operating system (most likely a real-time variant of the Linux Kernel) and of a lightweight middleware to enable an easy integration of software components.

Results: a working prototype drone, refined enough to allow the evaluation of its performance: maneuverability, stability, speed, energy efficiency, compatibility with mountain harsh environment, transportability.

Members of the research team in this task: Biral, Bosetti, Fontanelli, Migliaresi, Trivellato

  1. Mapping and Navigation

This Task is in charge of designing two main functions for fulfilling the desired goal: a) understanding the surrounding environment, b) locating possible victims, and c) autonomous navigation. 

According to the approaches discussed in the Project description, this central task hosts the development and preliminary testing of subsystems dedicated to ARVA beacon localization, self-localization and mapping of the surrounding environment, and algorithms for navigation and control of the drone. These activities are carried out on a functional subsystem approach: after designing a high-level architecture that defines the communication standards and interfaces, the three above named functions are individually developed and tested before integration.

Results: ARVA beacon signal processing algorithms for buried localization; image processing algorithms to define the context; a navigation algorithm for drones acting in harsh environments.

Members of the research team in this task: Melgani, Biral, Fontanelli, Palopoli

T 4 Smart Sensing

This task focuses on designing suitable sensing techniques that are specifically tailored to support drone navigation in avalanche areas. The presence of severe slopes or large obstacles (e.g., trees, rocks) and, more in general, the roughness of the surface due to the rubble transported by the avalanche itself, can indeed make drone navigation much more difficult than in usual scenarios. These problems are further emphasized by the strong requirement of flying steadily at a limited height (e.g., a few meters) above the avalanche to maximize the probability to detect the signal broadcasted by the ARVA device. 

The task on smart sensing will consists of the following subtasks:

  • Analysis and selection of different types of sensors to select the most suitable devices. Besides a GPS receiver coupled with an Inertial Measurement Unit (IMU) with a small form factor, an ultrasonic or a laser-based system are envisioned to scan the surface and to measure in real-time and with high accuracy (a few centimeters) both height-over-ground and distance from possible obstacles. A camera will be also included for context refinement and enhanced diagnostic capabilities in synergy with Task 3.
  • Development of a data fusion algorithm (e.g., an extended Kalman filter or an unscented Kalman filter) to estimate the 3-D position of the drone in the avalanche area. The area of search will be defined through the HMI. The algorithm should be robust even when the GPS data are not available.

Resultslist of sensors to be integrated on the drone; localization and position-tracking algorithm tested and characterized through simulations and preliminary experiments.

Members of the research team in this task: Macii, Fontanelli

  1. Human-Machine Interface

A main, tablet-based HMI is developed, allowing the drone operator to give a set of high-level directives and to access drone status information. In particular, the HMI must provide a way for quickly defining the boundary of the research area, the initial search direction, the patrolling height-over-ground, and other navigation parameters, and possibly to see on a local GPS-based map the location of beacons, updated as the drone localizes them. Effectiveness and viability of human spoken language interface (via portable radios that are common equipment for rescue teams) is also investigated and possibly implemented.

Results: prototype software to be deployed on tablet devices for controlling the drone.

Members of the research team in this task: Palopoli, Bosetti

  1. Test Facility

The hangar located in Pergine Valsugana, which is in the availabilities of DII, is equipped with devices and structures in order to allow indoor testing of drones in perfect safety for researchers and in conformity with the recent national regulations (which make relatively difficult outdoor testing). The hangar is a 25m x 40m space with a free height exceeding 20m. A large, yarn mesh surrounded volume is delimited within it, leaving small corridors around it for access, protecting the drone(s) from hitting people, equipment, or walls/ceilings. An inclined yarn mesh on the testing volume floor holding polyurethane foam blocks of various shapes can be used for simulating the uneven surface of an avalanche area. A suitable indoor localization system is selected and installed, in order to allow the simulation of a GPS-system and also providing a reliable ground-truth, essential for the testing phases. Other systems and infrastructures, as arrays of RGBD cameras also used for image recognition, WiFi networks, RFID beacons, are possibly also implemented, according to results of Task 1.

Results: a testing facility represented by a yarn-mesh surrounded isolated volume of about 20x30x20m3, equipped with 3-D localization system and other ground-based communication, computation, and measurement systems, according to results of Task 1.

Members of the research team in this task: Fontanelli, Biral, Bosetti, Macii, Melgani

  1. Integration

Subsystems of Tasks 3, 4, and 5 are integrated on the drone prototype resulting from Task 2. The resulting prototype is also integrated with subsystems and instrumentations of the testing facilities (with particular regards for the indoor localization system).

Results: A complete drone prototype, able to autonomously navigate within the testing facility, to localize an ARVA beacon, and to mark its position both physically (e.g., by a flag) and as its 3-D coordinates via HMI.

Members of the research team in this task: Bosetti, Fontanelli, Macii, Melgani, Migliaresi

  1. Testing

The prototype drone is run against the set of tests defined in Task 1, where it has to localize an ARVA beacon in the testing facility. The figure of quality is an index encompassing the time for localization, the accuracy and the repeatability of each localization, and the failure rate. The same tests are also performed by human ARVA operators to provide a reference benchmark.

Results: a set of statistics, showing how the prototype drone can improve the effectiveness of buried localization w.r.t. human ARVA operators.

Members of the research team in this task: Biral, All

  1. Legal analysis, Legal compliance, Interaction with Stakeholders, Dissemination

This task is collateral to all the other tasks of the project, and will cover the entire 18 months duration of the project, being divided in 2 phases: 12 months dedicated to legal analysis of issues in the Italian and European context; the following 6 months focusing on the legal compliance of the project, a task that will ease the dissemination of the project results with the external institutions involved and the stakeholders interested to the industrial exploitation of the project (CAI, Alpine Rescue Service, Police operators, ski area operators industry). The first phase will entail comparative research and critical evaluation of the legal sources applicable to drone operation and avalanche safety; and will culminate with the preparation of a study report. Building on the results of the first phase, the second phase will check the legal compliance of the project, envisaging internal seminars with the investigators responsible for the main task of the project, as well as workshop with stakeholders and end-users representatives, like the Italian Alpine Club (CAI), its local section SAT, and the Alpine Rescue Service, and ski area operator industry representatives, who will improve the solidity of the project assumptions with their knowledge about the real experience in carrying out a rescue operation for avalanche buried people.

Finally, An Advisory Board is appointed within this task, and involved in project by meeting with the project steering committee every six months. Also, fundraising and sponsorship opportunities are evaluated with the aim of providing continuity and successful exploitation during and after the project end.

Results: contributions to definition of requirements in Task 1, and continuous improvement throughout the project. Dissemination activities (papers, conferences, final event). Guidelines for legal aspects.

Members of the research team in this task: Izzo, Bosetti, Macii, Migliaresi