ARGOS (Autonomous UAV for Inspection and Monitoring in Confined Environments)

The project aims to develop an innovative Unmanned Aerial Vehicle (UAV) platform for inspections and surveying in complex industrial and natural environments, such as chemical plants, tunnels, penstocks, and geological sites. These contexts are characterized by confined spaces, lack of GNSS/GPS signals, variable lighting conditions, and obstacles that are not known in advance, making traditional inspection solutions ineffective and limiting the use of conventional drones.
The proposed solution will enable autonomous missions for surveying, infrastructure monitoring, and Search & Rescue operations, even in the absence of external localization infrastructure, ensuring safety and reliability of operations. 

Objectives

The project aims to develop an autonomous UAV capable of operating in confined environments without GNSS signal, with the following main tasks:

1. Autonomous localization: estimation of the UAV’s position using only onboard sensors, with integration through an Extended Kalman Filter. Two complementary approaches will be employed:
   • Lidar Inertial Odometry (LIO)
   • Visual Inertial Odometry (VIO)
     with the goal of achieving high accuracy and reliability beyond commercial standards.
     
     
2. Real-time mapping: creation of incremental 3D maps of the surrounding environment based on advanced SLAM algorithms, optimized for the selected sensors.
3. Obstacle avoidance: dynamic updating of the flight trajectory in the presence of obstacles, ensuring safety and successful completion of the overall mission.

Key Development Aspects:

• Accuracy: reduction of maneuvering margins and access to confined spaces through detailed mapping.
• Reliability: use of redundant and complementary sensors to ensure performance across different scenarios.
• Robustness: testing in environments with variable lighting, reflective surfaces, or non-standard features.
• Software speed: optimized processing for high update rates and reduced energy consumption.
• Versatility: interchangeable payload with different sensors for heterogeneous missions.

The project integrates hardware and software in an incremental approach, from sensor selection and calibration to the development of VIO, LIO, SLAM, and obstacle avoidance algorithms, culminating in experimental testing in controlled environments and real-world scenarios to validate performance against commercial solutions.

Project Details

Title: Autonomous UAV for Inspection and Monitoring in Confined Environments
Acronym: ARGOS
Funding Program: Autonomous Province of Bolzano – Simplified Experimental Development Projects – Act No. 66/2025
Total Budget: €50,000.00
MAVTech Budget: €50,000.00
Duration: January 2026 to December 2027

PARSIVAL (Aerial Platforms for Avalanche Search and Rescue)

Timeliness in avalanche Search and Rescue operations is of paramount importance for victim survival: the probability of rescuing alive a fully buried avalanche victim is around 80–90% in the first 15–20 minutes after burial, decreasing very rapidly thereafter. After 35 minutes, the survival probability drops drastically to about 30%.
This means that organized rescue teams often fail to arrive in time, and the survival of those victims depends almost exclusively on the expertise of the group members on site and, nonetheless, on the size and slope of the terrain affected by the avalanche.
The solution proposed in the PARSIVAL project will increase the chances of avalanche survival by promoting self-rescue, minimizing the time to locate buried victims, and reducing the probability of human error.

Objectives

The project involves the development of a lightweight (<1 kg), compact, and easily backpack-portable drone that, autonomously guided by a computer vision algorithm based on data from optical sensors and a miniaturized ARTVA device (avalanche beacon), can automatically locate any buried victim in an assisted rescue configuration and report the location to the 112 emergency center or to a search and rescue service.
If drone-guided self-rescue operations fail, further organized rescue actions can be taken, using multiple drones (equipped with optical and thermal sensors) flying simultaneously in swarm configuration.

To achieve this goal, the project activities include the development of:

• A small, lightweight, foldable, and portable aerial platform
• A miniaturized ARTVA sensor carried by the aerial platform
• A computational algorithm to define the boundaries of the search area and autonomously locate the victim(s), even on steeply sloping terrain
• A data support system (DSS) able to communicate between users and rescue operators (SAR). The DSS will coordinate other platforms (ground teams, helicopters, drones) to complete the rescue process

The developed solution will be validated through a field study, so to prove its effectiveness compared to traditional search methods and to evaluate its impact on the performance of companions and rescuers.
The project will contribute to sustainable development as promoted by the European Green Deal: it will improve the efficiency of search and rescue operations through low-environmental-impact platforms (electric-powered) and will reduce the use of more polluting platforms (helicopters) when not required.

Project Details

Title: Aerial Platforms for Avalanche Search and Rescue
Acronym: PARSIVAL
Project Code: EFRE1110
CUP: B57H25003290007
Funding Program: ERDF 2021–2027
Total Budget: €400,786.43 (Funded: €321,835.20)
MAVTech Budget: €197,378.08 (Funded: €118,426.85)
Partner: Eurac Research
Duration: 07/01/2026 – 12/31/2028

ITACA (Lighter-than-air Mobile Telecommunications Infrastructure for the Alpine Context) aims to study and develop a mobile telecommunications system that can be used in the aftermath of natural disasters (floods, landslides, avalanches, …) or in civil protection emergencies, to re-establish or create a new telecommunications infrastructure to serve mountain communities or rescue operators. It will also be applicable as a communication infrastructure for areas, particularly mountainous areas, not reached by communication technologies or to provide access to particular communication systems such as 5G.

The transport carrier will be an airship without a pilot on board, operating in automatic or tele-operated mode. The regulatory framework will be studied in order to include the aerostat in the UTM airspace. The limitations of use will be defined and the flight control system will be designed. An automatic or semi-automatic aerostat anchoring system will be designed, which allows the aerostat to maintain its pre-set geographical position. Transmission/connection methodology will be studied, also in multi-hop, to connect the communication system also to fixed infrastructures at great distances.

At least three demonstration sites will be identified through the NOI Techpark, in addition to the Corvara landslide site already taken as a reference for this project. The system will be developed jointly with the industrial and academic partners of Spoke 1 interested in the activity.

The ITACA project is carried out together with the partner FOS SpA.

OBJECTIVES

The ITACA project aims to develop a technology/airship without an on-board pilot that can be easily transported and installed in a strategic location to enable radio and communication links.

Expected outcomes

S.M.A.R.T. results of the ITACA project

• Specific: A UAS airship with a self-configuring telecommunications system will be built.
• Measurable: A demonstrator of the proposed infrastructure will be realised.
• Achievable: Previous knowledge and experience of the proposers in the design and development of UAS, telecommunication systems and in the integration of complex systems will be exploited.
• Relevant: Telecommunications recovery system in the event of an emergency.
• Time-Bound: We aim to present the demonstrator by March 2025.

Project details

Titolo: Infrastruttura di Telecomunicazioni mobile più leggera dell’Aria per il Contesto Alpino (Lighter-than-air Mobile Telecommunications Infrastructure for the Alpine Context)
Acronym: ITACA
Project ID: 2D1C29DF59
CUP: I59J24000290006
Funding Programme: iNEST
Overall Budget: € 364,859.50 (funded: € 248,080.76)
MAVTech Budget: € 211,372.00 (funded: € 147,131.80)
Partners: FOS SpA
Project Duration: 12.06.2024 – 31.10.2025

The system is designed to operate in emergency or civil protection scenarios, for example in the aftermath of natural disasters. It can also be deployed in areas — especially mountainous ones — that are not served by existing telecommunications infrastructure, providing access to advanced technologies such as 5G. Its integration was tested using the 5G router developed by Gruppo FOS and installed on board to ensure connectivity even in remote locations not covered by traditional networks.

First Flight Test – July 18, Ala di Stura (Turin)

After months of research, design, and development, the first operational test of the blimp took place on Thursday, July 18 at 1,000 meters above sea level, in the mountain town of Ala di Stura, in the province of Turin.

Second Flight Test – September 25, Cortaccia (BZ)

Third Flight Test – October 11, Malga Ciapela (BL)

The third and final flight test was conducted during the Pilot Day organized by the National Alpine and Speleological Rescue Corps of Belluno, held in Malga Ciapela (Belluno), which was also attended by INEST coordinator Daniele Cortolezzis.

These flights mark a concrete first step toward innovative and mobile telecommunications solutions, designed to respond quickly and flexibly in critical situations or geographically isolated locations.

For the survey activities, the MAVTech Q4X drone was used, equipped with the Altum PT multispectral sensor by AgEagle. This system makes it possible to capture both multispectral and RGB images, providing an in-depth view of the vegetative condition of urban flora. This approach enables the analysis of plant health and the early identification of critical situations, such as the risk of tree failure.

The project is based on a collaboration between MAVTech, the Municipality of Merano – Green Management and Environment Office and Studio Verde Torino. These two partners provide the technical skills and agronomic expertise essential for interpreting the collected data.

All the information gathered will be integrated into the GreenSpaces software by R3GIS, a platform dedicated to managing and documenting urban green maintenance activities. This integration will make it possible to generate detailed maps of the monitored areas.

The LEAFLET 2.0 (LightdronE Aerial support For pubLic grEen managemenT) project aims to develop a methodology and a service to support professional operators in the assessment of the health status and structural stability of public green areas, through the integration of data acquired by means of low-cost UAS (Unmanned Aerial System) platforms, WebGIS tools and through the use of Artificial Intelligence (AI) based techniques.

The continuous increase in the number of adverse climatic events, many of which are of an extreme nature, coupled with the constant ageing of tree installations in cities, leads the future of urban green management by technicians in the sector towards many challenges and associated risks. These risks derive from the possible dangers associated with the instability of trees in urban areas, due to unsuitable climatic conditions and improper maintenance of the same, which can lead to damage to property and above all to people, with consequent civil and criminal liability for those in charge of caring for them. In view of this, it is necessary to maximise the safety of urban green areas, ensuring that they are monitored and treated appropriately to avert any risk.

In order to do this, it is useful to clearly define standardised processes for the management of urban greenery, especially considering the aid of new technologies such as drones. This must include the description of procedures for planning the surveys, processing the acquired data, analysing the processed data and returning synthesised information through simplified tools to support professionals. In order to simplify the analysis and presentation of salient information to technicians, the LEAFLET2.0 project envisages the use of Artificial Intelligence (AI) and Machine Learning (ML) methodologies. These methodologies support the analysis of heterogeneous data (RGB, multispectral, LiDAR) and facilitate the rapid and automated generation of usable results for professionals.

Furthermore, in order to guarantee the creation of a complete and effective protocol, it is intended to directly involve local administrations in the study and definition processes, specifically the bodies in charge of monitoring, caring for and supervising urban green areas. Among these, for example, the green and environmental management office of the Municipality of Merano, which has shown its interest and availability towards the project, will certainly be involved, and the involvement of other offices dedicated to the management of public green areas of the South Tyrolean and national administrations will be evaluated.

Technical Objectives

• Identification of the type of data needed to correctly represent the phenomenon and/or the state of health of the individual plant and/or the generic vegetative state of an entire urban green area;
• Fine-tuning of the survey methodology, according to the specific in-depth study to be carried out;
• Streamlining of data processing procedures applied to date;Processing of Big data, definition of an application methodology;Interface between the LEAFLET2.0 application and WebGIS GreenSpaces
• Creation of thematic maps related to the analysis situation and definition of the significant outputs for the individual application cases and specific insights.

Innovation Objectives

• Integration of heterogeneous data: in particular, the innovative character resides in the identification of an application integration protocol between the analysis of data from different sensor sources, such as images from RGB cameras, multispectral sensors and LiDAR, also succeeding in integrating them and applying the Visual Tree Assessment (VTA) methodology.
• Integration of data from traditional surveys with high-resolution surveys carried out using UAS: the innovative character lies in the high potential for extending the possible studies that can be carried out, in addition to the representativeness that can be maintained by integrating traditional studies with the innovative ones; this aspect makes it possible to maintain a common thread between the monitoring data filed and recorded over the years in order to verify the correctness, consistency and continuity of the data and the innovative results obtained.
• Use of innovative Artificial Intelligence methodologies for the analysis of data, especially heterogeneous data, and Computer Vision for the correct alignment of nadiral photographs, with the aim of being taken precisely on the crowns of the plants.
• Simplification and automation of the process of compiling authorisation documents for flying in urban areas

Finally, part of the experimental project objectives will consider a validation of the survey results carried out also outside the province of Bozen/Bolzano. The activity will be punctual in order to explore meteorological and forest conditions that differ from the South Tyrolean context.

Project details

Title: LightdronE Aerial support For pubLic grEen managemenT
Acronym: LEAFLET2.0
Project Code: 244-22
CUP: B57H23000060001
Funding Programme: Autonomous Province of Bolzano (Provincial Law 13.12.2006, n. 14)
Overall Budget: € 220,300.00 (funded: € 220,300.00)
MAVTech Budget: € 90,135.00 (funded: € 90,135.00)
Consultants: Studio Verde, R3GIS, Flyingbasket.
Duration: 03.2023 – 12.2025