Drone Field Test
Early in November 2017, a field experiment was conducted to test integration of users’ smartphones and robotic drones into the HIRO-NET system. We used the standard Bridgefy app and a DJI Matrice 100 Quadcopter. The following video shows that drones can be effectively used as bridges to connect two or more disconnected users.
Testing HIRO-NET algorithms in MATLAB
In this video we show HIRO-NET performs clustering of the area affected by a natural disaster and computes the efficient flight plans for aerial drones. To optimize search and rescue operations, HIRO-NET partitions the city map into a Voronoi diagram each associated with a generating point. Generating points of Voronoi regions are rescue headquarter locations such as police stations, fire department, where HIRO-NET robotic platforms are initially stored. Upon activation, HIRO-NET drones take off from a rescue headquarter and fly within their Voronoi region to search for existing local mesh networks. HIRO-NET air drones are first directed to Points of Interest (PoI), which are predetermined areas such as schools, hospitals and stadiums. PoIs are assigned to each drone by using clustering algorithms (i.e., k-means). Graph theory optimization is applied to compute the optimal trajectory considering battery constraints. Each drone runs an online beaconing routine that discovers HIRO-NET mesh networks and dynamically updates its trajectory. The video also shows how aerial drones discover survivor-generated mesh networks and adapt their trajectory accordingly.