With the advent of small-scale autonomous flight we have witnessed amazing video footage. Often these small UAVs fly a pre-planned route set from the ground station and uploaded to the vehicle. The vehicle follows this route from start to finish recording video footage as it moves.
Route setting using a Ground Station software (Mission Planner)
Broad-Area flights are typically performed using wing aircraft which offer greater flight times and cover larger areas than multi-rotor vehicles
Moving forward from just recording video footage UAVs are increasingly being used in search and rescue situations. Winter proves particularly challenging for rescue workers to locate lost persons quickly and with minimal danger to life.
One of the challenges of using UAVs in search and rescue operations is that the operator must sit (or stand) during each flight and visually observe the flight footage in real-time in hope that they can detect a lost or injured person. This can be time consuming, causing the operator fatigue, tiredness, boredom, and eventually loss of interest in accurately detecting lost individuals.
This can have a negative impact on the search and rescue operation.
In the case of a Lost Female hiker in 2018 a drone operator flew, recorded and uploaded hours of recorded video footage hoping this would help in the location and detection of the missing hiker.
It is a challenging task which not only causes search fatigue, but can detract the search volunteers from continuing their search in organised groups believing that a drone is covering area. It is important to separate drone search from land search.
Automatic Person detection is emerging in robotics and UAV development, using small lightweight systems that incorporate object detection and classification algorithms. These systems are light enough to mount to fixed wing vehicles and embed into ground station hardware without significantly reducing flight times.
Here we can see the use of live object detection with a flight ground control system (APM Planner).
Mapping an autonomous flight path using a UAV Ground Station and launching the UAV, we can use the Person detection algorithm to take the hard work out of search and rescue drone flights.
We can read the serial data from the UAV and upon detection of a missing person, trigger a snap shot photo, record the GPS coordinates, and timestamp. This data can be recorded as .csv file
(Longitude, Latitude, Time, File Name)
Accuracy and detection threshold can be adjusted in the python .py file allowing the software to be customised according to how the terrain and conditions are affecting detection rates.
As an early stage proof of concept this is simply to demonstrate the possibility of Machine Learning and Artificial Intelligence in simplifying difficult tasks that may be too time consuming to be viable as a human-oriented task. Image quality and flight altitude will factor towards detection accuracy, as will weather and landscape conditions. However, by using this in a methodical and co-ordinated setup utilising multiple UAV each using a different flight pattern we could potentially reduce search and rescue times over challenging terrain environments.
Links:
https://dronebelow.com/2018/11/20/drones-swarms-and-ai-for-search-and-rescue-operations-at-sea/
