DIFPL - Distributed Drone Flight Path Builder System

Shukla, Manu; Chen, Ziqian; Lu, Chang-Tien

doi:10.5220/0005378700170026

Cited by 2 publications

(1 citation statement)

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“…None of the techniques proposed so far has the capacity to build coordinated flight paths for fleet of drones that will enable them to perform a complex survey task in a distributed co-ordinated performant manner. DIMPL, like an earlier prototype DIFPL [38], does not rely on images or video to navigate. Instead flight paths are built offline using terrain and network line data and do not need to be adjusted dynamically as all the constraints are applied when the program is run.…”

Section: Related Workmentioning

confidence: 99%

DIMPL: a distributed in-memory drone flight path builder system

Shukla¹,

Chen

2018

J Big Data

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As use of drones rapidly expands, it is aided by improvements in technology such as high speed cameras, sensors, and processors able to analyze the data rapidly and efficiently on the drone. Better scalability in processing image, terrain, weather and surface data and using it to aid in navigation has also allowed them to become increasingly autonomous during flight. Drones have proven very useful in both military battlefield and civilian tasks. Along with common civilian tasks in education [30], studying natural phenomena [45], reconnaissance [36] and conservation [28] they have been used increasingly in surveying farms [41], forests [10] and borders [27]. Drones can either be controlled manually by an operator or fly autonomously, but as the use for an operator increases the cost considerably, it is clearly preferable for them to operate autonomously. Autonomous flight presents challenges in terrain navigation, however, as a multitude of flight path scenarios such as variations in altitude and the density of objects to be surveyed must be taken into account. Flight planning

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Section: Related Workmentioning

confidence: 99%