NDLI: Real-world Drone Sensor Networks: A Multi-disciplinary Challenge

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Real-world Drone Sensor Networks: A Multi-disciplinary Challenge

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Real-world Drone Sensor Networks: A Multi-disciplinary Challenge

Content Provider	ACM Digital Library
Author	Mottola, Luca
Abstract	Autonomous drones are emerging as a powerful new breed of mobile sensing system. Small embedded computers that move almost unconstrained while carrying rich sensor payloads, such as cameras and microphones, bring sensing and actuation where no other technology can reach. Aerial, ground, and aquatic drones are available off-the-shelf and often come with a simple abstraction for navigation. Many of them can be controlled by setting waypoints or by manually steering using a graphical interface; for example, using a tablet or a smartphone. As new designs emerge, drones progressively achieve higher speeds, carry larger payloads, and cover larger distances on batteries. Notwithstanding the most recent advancements, the current use of drone technology is often limited to manual control of individual devices by skilled individuals. The gap between this and large-scale autonomous operation in real-world scenarios remains significant. The challenges at stake span diverse disciplines, including automatic control, computer vision, software development, and mechanical engineering. To complicate matters, the existing regulations are often not fully cognizant of the characteristics of the technology, and run the risk of becoming a hampering factor. We have first-hand experience of this state of affairs, gained through several efforts in a range of real-world applications, including aerial photogrammetry and 3D reconstruction. The talk will report on these experiences, describe the research work we conducted to overcome the issues at hand, and point out the several open problems still existing in this field.
Starting Page	1
Ending Page	1
Page Count	1
File Format	PDF
ISBN	9781450338400
DOI	10.1145/2820990.2820991
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2015-11-01
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Applications Coordination Real world Sensing Drones
Content Type	Text
Resource Type	Article

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