Online Path Generation and Navigation for Swarms of UAVs

Adnan Ashraf, Amin Majd, Elena Troubitsyna

Research output: Contribution to journalArticleScientificpeer-review

1 Citation (Scopus)
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Abstract

Withthe growing popularity of Unmanned Aerial Vehicles (UAVs) for consumerapplications, the number of accidents involving UAVs is also increasingrapidly. 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 preventingthe UAVs from colliding with one another and with static and dynamicallyappearing, moving obstacles in the flying zone. In this paper, we present anonline, collision-free path generation and navigation system for swarms ofUAVs. The proposed system uses geographical locations of the UAVs and of thesuccessfully 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-obstaclecollisions. Our collision prediction approach leverages efficient runtimemonitoring and Complex Event Processing (CEP) to make timely predictions. Adistinctive feature of the proposed system is its ability to foresee potentialcollisions and proactively find best ways to avoid predicted collisions inorder to ensure safety of the entire swarm. We also present a simulation-basedimplementation of the proposed system along with an experimental evaluationinvolving a series of experiments and compare our results with the results offour existing approaches. The results show that the proposed system successfullypredicts and avoids all three kinds of collisions in an online manner.Moreover, it generates safe and efficient UAV routes, efficiently scales tolarge-sized problem instances, and is suitable for cluttered flying zones andfor scenarios involving high risks of UAV collisions.

Original languageUndefined/Unknown
Pages (from-to)1–14
JournalScientific Programming
Volume2020
DOIs
Publication statusPublished - 2020
MoE publication typeA1 Journal article-refereed

Keywords

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

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