Research on vision navigation and position system of agricultural unmanned aerial vehicle

References

• Alexey, Y., S. V. Aksenov, and A. Kuleshov. 2014. “An Application of Computer Vision Systems to Solve the Problem of Unmanned Aerial Vehicle Control.” Transport and Telecommunication Journal 31: 209–214.
   Google Scholar
• Araar, O., and N. Aouf. 2015. “Practical Servoing of VTOL UAVs from Object of Unknown 3D Geometry: New Hybrid Approach.” The Imaging Science Journal 63 (8): 476–487. doi:10.1179/1743131X15Y.0000000023.
   Web of Science ®Google Scholar
• Barry, A., P. R. Florence, and R. Tedrake. 2018. “High Speed Autonomous Obstacle Avoidance with Push Broom Stereo.” Journal of Field Robotics 35 (1): 52–68. doi:10.1002/rob.21741.
   Web of Science ®Google Scholar
• Brantley, S. T. 2011. “Application of Hyperspectral Vegetation Indices to Detect Variations in High Leaf Area Index Temperate Shrub Thicket Canopies.” Remote Sensing of Environment 15 (2): 514–521. doi:10.1016/j.rse.2010.09.020.
   Google Scholar
• Canny, J. 1986. “A Computational Approach to Edge Detection.” IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI-8 (6): 679–698. doi:10.1109/TPAMI.1986.4767851.
   Web of Science ®Google Scholar
• Castro, K. L. 2018. “Changes in Spectral Properties, Chlorophyll Content and Internal Mesophyll Structure of Sensing Populus Balsamifera and Populus Tremuloides Leaves.” Sensors 2: 51–56.
   Google Scholar
• Chen, M., and W. Hu. 2019. “Research on BatSLAM Algorithm for UAV Based on Audio Perceptual Hash Closed-Loop Detection.” International Journal of Pattern Recognition and Artificial Intelligence 33 (1): 793–798. doi:10.1142/S021800141959002X.
   Web of Science ®Google Scholar
• Darvishzadeh, R. 2008. “Lai and Chlorophyll Estimation for a Heterogeneous Grassland Using Hyperspectral Measurements.” ISPRS Journal of Photogrammetry and Remote Sensing 7 (4): 409–426. doi:10.1016/j.isprsjprs.2008.01.001.
   Google Scholar
• Davison, A., M. Nicholas, and S. Olivier. 2007. “MonoSLAM: Real-timesingle Camera SLAM.” IEEE Transactions on Pattern Analysis and Machine Intelligence 29 (6): 1052–1067. doi:10.1109/TPAMI.2007.1049.
   PubMed Web of Science ®Google Scholar
• Delalieux, S. 2008. “A Near-infrared Narrow-waveband Ratio to Determine Leaf Area Index in Orchards.” Remote Sensing of Environment 43 (10): 3762–3772. doi:10.1016/j.rse.2008.05.003.
   Google Scholar
• Franchi, A., C. Masone, V. Grabe, M. Ryll, H. H. Bülthoff, and P. R. Giordano. 2012. “Modeling and Control of UAV Bearing Formations with Bilateral High-level Steering.” The International Journal of Robotics Research 31 (12): 1504–1525. doi:10.1177/0278364912462493.
   Web of Science ®Google Scholar
• Ivan, H., and Beloev. 2016. “A Review on Current and Emerging Application Possibilities for Unmanned Aerial Vehicles.” Act a Technologic a Agriculturae: 70–76.
   Google Scholar
• Jago, R. A. M., and E. J. Cutler.. 1999. “Estimating Canopy Chlorophyll Concentration from Field and Airborne Spectra.” Remote Sensing of Environment 60 (3): 217–224. doi:10.1016/S0034-4257(98)00113-8.
   Google Scholar
• Lagüela, S., L. Díaz, and D. Vilariño. 2015. “Aerial Thermography from Low-cost UAV for the Generation of Thermographic Digital Terrain Models.” Ospto-Electronics Review 7: 78–84.
   Google Scholar
• Li, C., Y. C. Zhang, and T. Lan. 2018. “An Object Detection Algorithm with Visual Perception for High-resolution Remote Sensing Images.” Journal of Xi, an Jiaotong University 52: 9–16.
   Google Scholar
• Lihong, X., and Y. Linzhang. 2009. “Deriving Leaf Chlorophyll Content of Green-leafy Vegetables from Hyperspectral Reflectance.” ISPRS Journal of Photogrammetry and Remote Sensing 55: 97–102.
   Google Scholar
• Loquercio, A., A. I. Maqueda, and C. R. Del-Blanco. 2018. “DroNet: Learning to Fly by Driving.” IEEE Robotics and Automation Letters 3 (2): 1088–1095. doi:10.1109/LRA.2018.2795643.
   Web of Science ®Google Scholar
• Mirosław, R. 2012. “Airworthiness Tests of the UAV Structure − Fatigue Issues.” Platt formfürMethoden, Systeme und Anwendungen der Messtechnik 35: 503–507.
   Google Scholar
• Qin, C., Z. Meng, and W. Meng. 2019. “Autonomous Exploration and Mapping System Using Heterogeneous UAVs and UGVs in GPS-Denied Environments.” IEEE Transactions on Vehicular Technology 68 (2): 1339–1350. doi:10.1109/TVT.2018.2890416.
   Web of Science ®Google Scholar
• Qin, T., P. Li, and S. Shen. 2018. “VINS-Mono:A robust and Versatile Monocular Visual-inertial State Estimator. ”IEEE Transactions on Robotics 34: 1004–1020. doi:10.1109/TRO.2018.2853729.
   Web of Science ®Google Scholar
• Shah, S., D. Dey, and C. Lovett. 2018. AirSim: High-fidelityv isual and Physical Simulation for Autonomous Vehicles, 621–635. Zurich, Switzerland: Field and Service Robotics.
   Google Scholar
• Trujillo, J. C., R. Munguia, and E. Guerra. 2018. “Visual-Based SLAM Configurations for Cooperative Multi-UAV Systems with a Lead Agent: An Observability-Based Approach.” Sensors (Basel, Switzerland) 18 (12): 1424–8220. doi:10.3390/s18124243.
   Web of Science ®Google Scholar
• Zarco, T. P. J., and J. R. Miller. 2001. “Scaling-up and Model Inversion Methods with Narrowband Optical Indices for Chlorophyll Content Estimation in Closed Forest Canopies with Hyperspectral Data.” IEEE Transactions on Geoscience and Remote Sensing 39 (7): 1491–1496. doi:10.1109/36.934080.
   Web of Science ®Google Scholar
• Zhu, Z., Taylor, and C. Taylor. 2017. “Conservative Uncertainty Estimation in Map-Based Vision-Aided Navigation.” IEEE Transactions on Aerospace and Electronic Systems 53 (2): 941–949. doi:10.1109/TAES.2017.2667278.
   Web of Science ®Google Scholar