Research Project “DRONES FOR FINDING AVALACHE-BURIED” (D-FAB)
A person buried by a snow avalanche can be found by measuring the magnetic field generated by an avalanche beacon or ARVA carried by the victim. However, the signals received are difficult to interpret and require people with good training on the actual searching techniques. Even in this case, though, the find and rescue operation can be significantly slowed down by the typically steep, rough, and uneven ground of an avalanche area. Given the fact that the probability of survival drops from 90% to 30% between 18 and 30 min after the event, any technology that can speed up the spotting of the beacon signal can effectively reduce the death risk for buried people.
We propose to develop a hexacopter drone for helping the rescue team in finding and marking the positions of buried people. Such a drone would carry an ARVA receiver, a collection of systems for mapping, localization, navigation, and attitude/cruise control, and a device for physically marking the position of buried ARVA beacons (e.g., by dropping a flag, by paint-marking, etc.). The rescue team would launch the drone upon arrival on the avalanche scenario and define a geographic boundary for the search area by means of a proper remote interface with the drone controller. As soon as the drone localizes and marks the first beacon, the rescue team can start digging around the first mark, while the drone proceeds in searching for possible other beacon signals. In terms of time efficiency, this scenario has a two advantages: firstly, given that the speed of the drone largely exceeds that of human rescuers—especially considering the uneven and steep ground they are typically moving on—, the beacon localization time can be significantly reduced; secondly, the search for any subsequent buried people can happen in parallel while the rescue team is busy digging, not to mention that a swarm of drones can prove even more effective in compressing the average finding time.
Development of such a system is a highly interdisciplinary task, demanding for competences in mechatronics, automation, control, measurements, signal processing, and tackling of possible legal issues. To date, there are no examples of similar systems on the market, although there are very recent and ongoing research efforts with similar objectives triggered by the recent fast developments in the market of small UAVs. We reckon that this is the right time for starting research activities in this field within our University, for three reasons: i) technology readiness: small robotic drones and UAVs can be realized at reasonable costs; ii) competences: after the recent rearrangement of university Departments, we have now most of the competences of interest in this field in a contiguous space (Povo 2 building, hosting both the Dpt. of Industrial Engineering and the Dpt. of Information Engineering and Computer Science); iii) a large, indoor space suitable to be equipped as a drone testing area has been recently made available to the DII.