Online Path Generation and Navigation for Swarms of UAVs

A1 Originalartikel i en vetenskaplig tidskrift (referentgranskad)


Interna författare/redaktörer


Publikationens författare: Adnan Ashraf, Amin Majd, Elena Troubitsyna
Förläggare: Hindawi Publishing Corporation
Publiceringsår: 2020
Tidskrift: Scientific Programming
Volym: 2020
Artikelns första sida, sidnummer: 1
Artikelns sista sida, sidnummer: 14
eISSN: 1875-919X


Abstrakt

With
the growing popularity of Unmanned Aerial Vehicles (UAVs) for consumer
applications, the number of accidents involving UAVs is also increasing
rapidly. Therefore, motion safety of UAVs has become a prime concern for UAV operators.
For a swarm of UAVs, a safe operation can not be guaranteed without preventing
the UAVs from colliding with one another and with static and dynamically
appearing, moving obstacles in the flying zone. In this paper, we present an
online, collision-free path generation and navigation system for swarms of
UAVs. The proposed system uses geographical locations of the UAVs and of the
successfully detected, static and moving obstacles to predict and avoid: (1)
UAV-to-UAV collisions, (2) UAV-to-static-obstacle collisions, and (3) UAV-to-moving-obstacle
collisions. Our collision prediction approach leverages efficient runtime
monitoring and Complex Event Processing (CEP) to make timely predictions. A
distinctive feature of the proposed system is its ability to foresee potential
collisions and proactively find best ways to avoid predicted collisions in
order to ensure safety of the entire swarm. We also present a simulation-based
implementation of the proposed system along with an experimental evaluation
involving a series of experiments and compare our results with the results of
four existing approaches. The results show that the proposed system successfully
predicts and avoids all three kinds of collisions in an online manner.
Moreover, it generates safe and efficient UAV routes, efficiently scales to
large-sized problem instances, and is suitable for cluttered flying zones and
for scenarios involving high risks of UAV collisions.


Nyckelord

Collision avoidance, Complex event processing, Path planning, Robotics and automation, Swarm of drones, UAV


Dokument


Senast uppdaterad 2020-16-02 vid 06:41