Journal
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS
Volume 20, Issue 5, Pages 1735-1744Publisher
INST CONTROL ROBOTICS & SYSTEMS, KOREAN INST ELECTRICAL ENGINEERS
DOI: 10.1007/s12555-020-0586-3
Keywords
Deep learning; landing mark detection; multirotor; UAV; vision-based landing guidance; vision-impairment environments
Categories
Funding
- National Research Foundation of Korea (NRF) - Ministry of Science and ICT of Korea (MSIT) [NRF-2018M2C7A1A02071506]
- Creative Economy Leading Technology Development Program through the Gyeongsangbuk-Do and Gyeongbuk Science & Technology Promotion Center of Korea [SF318002A]
- Korea Agency for Infrastructure Technology Advancement (KAIA) - Ministry of Science and ICT/Ministry of Trade, Industry and Energy/Ministry of Land, Infrastructure and Transport [19DPIW-C153675-01]
- National Research Foundation of Korea [2018M2C7A1A02071506] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
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A novel landing concept with deep learning technique is proposed in this study, which successfully guided multicopter landing in vision-impaired environments.
Most vision-based landing algorithms cannot be applied in a severe vision-detection environment. However, the application of a deep learning technique to vision-based landing algorithm can solve the problem of a severe vision-detection environment, especially in vision-impaired environments. Based on this fact, a novel-landing concept with deep learning technique is proposed in this study. Three main techniques applied for guided landing are 1) deep learning for accurate landing mark detection; 2) location-memorized system for coping temporal failure of the landing mark detection; 3) Unmanned Aerial Vehicle control algorithm for vibration minimization in vision sensor. The proposed system successfully and accurately guided the multicopter onto the landing area without failure in vision-impaired environments. The results show that the proposed landing algorithm can overcome environmental restrictions in operating multicopters.
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