Open AccessAutonomous trail‐following unmanned aerial vehicle system based on resource partitioning of single hardware platform
Author(s) -
Lim Yoojin,
Kim Kyungil,
Shin Jinah,
Lim Chaedeok
Publication year - 2021
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/ell2.12099
Subject(s) - overhead (engineering) , computer science , real time computing , embedded system , domain (mathematical analysis) , resource (disambiguation) , field (mathematics) , artificial intelligence , computer network , operating system , mathematical analysis , mathematics , pure mathematics
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—in a bid to reduce flight risk—is 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—in that the workloads incur minimal communication delay—between 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.