NDLI: Towards a realtime, collision-free motion coordination and navigation system for a UAV fleet

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Towards a realtime, collision-free motion coordination and navigation system for a UAV fleet

Content Provider	ACM Digital Library
Author	Ashraf, Adnan Majd, Amin Troubitsyna, Elena
Abstract	This paper presents a realtime, collision-free motion coordination and navigation system for an Unmanned Aerial Vehicle (UAV) fleet. 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 a risk of a collision in realtime and proactively find best ways to avoid the predicted collisions in order to ensure safety of the entire fleet. We also present a simulation-based implementation of the proposed system along with an experimental evaluation involving a series of experiments. The results demonstrate that the proposed system successfully predicts and avoids all three kinds of collisions in realtime. Moreover, it generates efficient UAV routes, has an excellent runtime performance, efficiently scales to large-sized problem instances involving dozens of UAVs and obstacles, and is suitable for some densely populated, cluttered flying zones.
Starting Page	1
Ending Page	9
Page Count	9
File Format	PDF
ISBN	9781450348430
DOI	10.1145/3123779.3123805
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2017-08-31
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Fleet Navigation Motion coordination Complex event processing Path planning Uav Drone Collision avoidance Quadrotor
Content Type	Text
Resource Type	Article

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