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Journal Article
Autonomous trail‐following unmanned aerial vehicle system based on resource partitioning of single hardware platform
- Authors
- Yoojin Lim, Kyungil Kim, Jinah Shin, Chaedeok Lim
- Issue Date
- 2021-03
- Citation
- Electronics Letters, v.57, no.6, pp.245-248
- ISSN
- 0013-5194
- Publisher
- IET
- Language
- English
- Type
- Journal Article
- Abstract
- As deep neural networks are spreading to almost all fields, flight systems in the unmanned aerial vehicle (UAV) domain are undergoing various transitions to intelligent systems. Among these transitions?봧n a bid to reduce flight risk?봧s the active research domain of autonomous navigation for intelligent UAVs. The autonomous trail-following flight system that this letter introduces can safely consolidate flight control and mission control within the latest commercial hardware platform. The resource usage and degradation of pass-through delay in vision-based convolutional neural network workloads show that virtualisation overhead is not significantly negative, and the overall performance of the introduced system is acceptable. Real-time cooperation is also verified as achievable?봧n that the workloads incur minimal communication delay?봟etween the controls. Finally, the actual field test analysis demonstrates the applicability of our autonomous UAV system, whereby our system controls the UAV to follow the centre of a set trail.
- KSP Keywords
- Autonomous UAV system, Convolution neural network(CNN), Deep neural network(DNN), Field Test, Flight risk, Flight systems, Hardware platform, Mission control, Overall performance, Real-time cooperation, Resource Usage
This work is distributed under the term of Creative Commons License (CCL)
(CC BY)
(CC BY)
