Article
Engineering, Multidisciplinary
Bai TingTing, Wang DaoBo, Rana Javed Masood
Summary: In this article, the authors design a formation control system for quad-rotor UAVs using pigeon inspired optimization (PIO) and nonlinear mathematical models. The algorithm uses position deviation matrices to describe formation and dynamically adjusts weight coefficients to control inertia. SIMULINK-based simulations show successful formation control of the UAVs with the help of PIO.
SCIENCE CHINA-TECHNOLOGICAL SCIENCES
(2022)
Article
Engineering, Aerospace
SunHoo Park, Sihun Lee, Byeonguk Im, Dongyeol Lee, SangJoon Shin
Summary: This study develops an improved real-time flight simulation to predict the transient response of a multi-rotor UAV influenced by gust induced by buildings. The simulation couples unsteady rotor aerodynamics with nonlinear flight dynamics to accurately predict the UAV's response to gust. It also proposes a gust estimation approach based on nonlinear flight dynamics to consider the influence of unidentified gust. The proposed flight simulation is validated through gust experiments and is found to correlate well with the experiments.
AEROSPACE SCIENCE AND TECHNOLOGY
(2023)
Article
Engineering, Electrical & Electronic
Fabian T. Faul, Daniel Korthauer, Thomas F. Eibert
Summary: In near-field measurements, correcting for probe influence is crucial for achieving high accuracy, particularly in the field of antenna measurements based on unmanned aerial vehicles. Research shows that modulation caused by rotating rotor blades of UAVs is dependent on probe antenna polarization, spatial separation from the UAV, and rotor rotation speed, but independent of the actual measurement frequency.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2021)
Article
Automation & Control Systems
Shengming Li, Zongyang Lv, Lin Feng, Yuhu Wu, Yingshun Li
Summary: This paper proposes a nonlinear control strategy for a newly-designed coaxial tilt-rotor unmanned aerial vehicle (UAV). The proposed strategy includes two sub-controllers, an inner-loop attitude controller and an outer-loop velocity controller, which are designed using a backstepping-like feedback linearization method.
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS
(2022)
Article
Automation & Control Systems
Zong-Yang Lv, Yuhu Wu, Qing Zhao, Xi-Ming Sun
Summary: In this article, the design and control of a novel coaxial tilt-rotor unmanned aerial vehicle (CTRUAV) are discussed. The CTRUAV, composed of two pairs of tiltable coaxial rotors and a rear rotor, has been designed using 3-D computer-aided design software and constructed according to the designing scheme. The dynamic model of the CTRUAV is derived using the Euler-Lagrange equation, and an adaptive controller is developed for motion control. The stability of the closed-loop CTRUAV system is analyzed, and simulations and real experiments are conducted to validate the effectiveness of the system.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2022)
Article
Computer Science, Information Systems
Miaoxin Pan, Chongcheng Chen, Xiaojun Yin, Zhengrui Huang
Summary: This study proposes a UAV-aided emergency environmental monitoring system using a LoRa mesh networking approach for rapid data transmission. Experimental results show that the system has high data transmission speed, real-time response, and good network robustness.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Engineering, Aerospace
Yunjie Yang, Jihong Zhu, Xiangyang Wang, Xiaming Yuan, Xiaojun Zhang
Summary: This paper investigates the dynamic model, transition corridors, and control strategy for a rotor-blown-wing tail-sitter, developing novel dynamic transition corridors and enhancing them with climb velocity constraints to improve transition robustness. The transition strategy and controller are constructed based on the optimal transition trajectories to keep the transition trajectory in the middle of the enhanced corridors, resulting in a more robust and natural flight compared to constant altitude or large altitude climb transitions. Flight test results demonstrate the design principles, transition strategy, and controller of the tail-sitter.
JOURNAL OF GUIDANCE CONTROL AND DYNAMICS
(2021)
Article
Agriculture, Multidisciplinary
Wanxue Zhu, Zhigang Sun, Yaohuan Huang, Ting Yang, Jing Li, Kangying Zhu, Junqiang Zhang, Bin Yang, Changxiu Shao, Jinbang Peng, Shiji Li, Hualang Hu, Xiaohan Liao
Summary: This study utilized UAV data for maize phenotyping, revealing the advantages of both single-source and multi-source UAV data in different aspects. The optimal UAV combination for accurate agro-monitoring was determined to be LiDAR, RGB, and hyperspectral, highlighting the importance of UAV technologies in precision agriculture.
PRECISION AGRICULTURE
(2021)
Article
Automation & Control Systems
Gang Li, Bin He, Zhipeng Wang, Xu Cheng, Jie Chen
Summary: A blockchain-enhanced data collection framework for UAV-assisted WSNs is proposed in this article, which effectively increases the network life cycle and data reconstruction accuracy by optimizing the data aggregation model and the identity authentication mechanism, and accurately describes the disaster situation through the disaster semantic blockchain.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Environmental Sciences
Yuqi Liu, Change Zheng, Xiaodong Liu, Ye Tian, Jianzhong Zhang, Wenbin Cui
Summary: Forest fires pose a significant global threat, and this study presents a method to identify them by fusing visual and infrared images. By addressing the limitations of using single spectral imagery, such as high false alarm and missed alarm rates, the proposed FF-Net achieves higher accuracy in detecting forest fires. The results demonstrate a false alarm rate of 0.49% and a missed alarm rate of 0.21%, highlighting the importance of using fused images for early warning of forest fires.
Review
Environmental Sciences
Oktawia Lewicka, Mariusz Specht, Andrzej Stateczny, Cezary Specht, Gino Dardanelli, David Brcic, Bartosz Szostak, Armin Halicki, Marcin Stateczny, Szymon Widzgowski
Summary: This paper presents an integrated data model for bathymetric monitoring system in shallow waterbodies using Unmanned Aerial Vehicles (UAV) and Unmanned Surface Vehicles (USV). The model utilizes different technology components to cover the entire coastal area with high measurement accuracy, meeting the requirements set by the International Hydrographic Organization (IHO) for human safety and environmental protection.
Article
Geography, Physical
Jiale Jiang, Kasper Johansen, Yu-Hsuan Tu, Matthew F. McCabe
Summary: Unmanned aerial vehicle (UAV) and satellite data have complementarity in terms of spectral characteristics and compatibility, but there may be spectral and spatial misalignments between them. This study assessed the spectral consistency between UAV and satellite multispectral imagery and found that radiometric correction and different ground features can affect their spectral consistency. It also discovered that spatial scale differences can impact the consistency between UAV and satellite data.
GISCIENCE & REMOTE SENSING
(2022)
Article
Chemistry, Analytical
Deyi You, Yongping Hao, Jiulong Xu, Liyuan Yang
Summary: In this study, a pose estimation algorithm based on unscented Kalman filter information fusion is proposed to address the problem of inaccurate attitude measurement by the single sensor of the coaxial UAV. The kinematics and dynamics characteristics of the coaxial folding twin-rotor UAV are investigated, and a mathematical model is established. The common attitude estimation methods are analyzed, and the extended Kalman filter algorithm and unscented Kalman filter algorithm are developed. A test platform for the dynamic performance and attitude angle of the semi-physical flight of the UAV is established, which allows analysis of mechanical vibration, attitude angle, and noise of the aircraft. The experiment and analysis provide insights for optimizing the control parameters and flight control strategy of the coaxial folding dual-rotor aircraft.
Article
Environmental Sciences
Yong Chen, Xiaoxu Zhang, Xiaofeng Wu, Jia Li, Yang Qiu, Hao Wang, Zhang Cheng, Chengbin Zheng, Fumo Yang
Summary: An unmanned aerial vehicle system was designed for monitoring and sampling volatile organic compounds in the atmosphere, demonstrating potential in environmental monitoring through optimized sampling conditions and comparison experiments.
Article
Biodiversity Conservation
Yi Xiao, Jiahao Chen, Yue Xu, Shihui Guo, Xingyu Nie, Yahui Guo, Xiran Li, Fanghua Hao, Yongshuo H. Fu
Summary: In recent decades, the proliferation of phytoplankton and sediment input into rivers, especially urban rivers, has become more severe under the compound pressure of climate change and human activities. With the limitations of satellite band settings, bandwidth, and the signal-to-noise ratio, unmanned aerial vehicles (UAVs) with exceptional spatiotemporal resolution can be used as a useful tool for river environmental monitoring and inversion uncertainty assessment.
ECOLOGICAL INDICATORS
(2023)
Article
Plant Sciences
Farida Abubakari, Philip Nti Nkrumah, Denise R. Fernando, Peter D. Erskine, Antony van der Ent
Summary: This study found that wild M. ternifolia and M. integrifolia are strong Mn accumulators, and M. integrifolia and M. tetraphylla also exhibit high Mn accumulation under experimental conditions. The efficient translocation of Mn from roots to shoots was demonstrated in the studied species.
ENVIRONMENTAL AND EXPERIMENTAL BOTANY
(2022)
Article
Agronomy
Antony van der Ent, Yohan Pillon, Bruno Fogliani, Vidiro Gei, Tanguy Jaffre, Peter D. Erskine, Guillaume Echevarria, Kathryn M. Spiers, Adrian L. D. Paul, Sandrine Isnard
Summary: The Cunoniaceae in New Caledonia have 91 endemic species that hyperaccumulate multiple metals, making them an ideal model system for studying the hyperaccumulation phenomenon. XRF scanning revealed differences in Mn and Ni accumulation in different species, with Pancheria reticulata showing Mn concentration in hypodermal cells and P. xaragurensis mainly accumulating Ni in and around the epidermis. This suggests different ecophysiological adaptations in these species.
Article
Ecology
Phillip B. McKenna, Alex M. Lechner, Lorna Hernandez Santin, Stuart Phinn, Peter D. Erskine
Summary: This paper evaluates the capability of remote sensing data for monitoring ecosystem restoration and proposes a combination of remote sensing with the ecological recovery wheel (ERW) for improved restoration outcomes.
RESTORATION ECOLOGY
(2023)
Article
Environmental Sciences
Philip Nti Nkrumah, Guillaume Echevarria, Peter D. Erskine, Antony van der Ent
Summary: There is a global trend towards electric vehicles to combat climate change, which will greatly increase the demand for critical metals used in batteries. Agromining technology offers a sustainable solution by extracting high-purity metal salts from selected plants, thus providing a green source for green technologies.
SCIENCE OF THE TOTAL ENVIRONMENT
(2022)
Article
Environmental Sciences
Amarasingam Narmilan, Felipe Gonzalez, Arachchige Surantha Ashan Salgadoe, Unupen Widanelage Lahiru Madhushanka Kumarasiri, Hettiarachchige Asiri Sampageeth Weerasinghe, Buddhika Rasanjana Kulasekara
Summary: This research utilizes unmanned aerial vehicles and spectral vegetation indices to infer chlorophyll content in sugarcane crops and compares the performance of multiple machine learning algorithms in predicting chlorophyll content. The findings demonstrate the accuracy of estimating chlorophyll content using multispectral UAVs and emphasize the importance of this methodology in crop nutrition management in sugarcane plantations.
Article
Plant Sciences
Antony van der Ent, Kathryn M. Spiers, Dennis Brueckner, Peter D. Erskine
Summary: This study used synchrotron X-ray fluorescence micro-computed tomography to elucidate the distribution of nickel in the hyperaccumulator plant Stackhousia tryonii. The results showed nickel mainly concentrated in apoplastic space surrounding epidermal cells and epidermal cell vacuoles, highlighting the utility of XFM-CT for visualizing metals within intact plant organs.
AUSTRALIAN JOURNAL OF BOTANY
(2022)
Review
Ecology
Mitchel L. M. Rudge, Shaun R. Levick, Renee E. Bartolo, Peter D. Erskine
Summary: This article explores practical options for creating landscape-scale forest restoration targets that embrace spatial pattern. Hierarchy theory, satellite remote sensing, landscape pattern analysis, drone-based remote sensing, and spatial point pattern analysis are all useful tools for assessing and quantifying the spatial pattern of reference landscapes and informing forest restoration targets.
Article
Agronomy
Roger H. Tang, Philip N. Nkrumah, Peter D. Erskine, Antony van der Ent
Summary: The study aimed to investigate zinc-cadmium tolerance in C. novae-hollandiae and compare it with C. cunninghamii. The results showed that C. novae-hollandiae accumulated high levels of zinc and cadmium in its shoots, with an increase in biomass. However, its tolerance for cadmium was limited. This study also suggested that C. novae-hollandiae may have different mechanisms for element uptake and tolerance compared to other well-studied zinc-cadmium hyperaccumulators.
Article
Environmental Sciences
Alison Carver, Miguel Alvarado Molina, Joep L. A. Claesen, Gonnie Klabbers, David Donaire, Gonzalez, Rachel Tham, Ester Cerin, Mark Nieuwenhuijsen, Amanda J. Wheeler
Summary: This study found that vegetation around primary schools in urban areas of Australia is positively associated with higher academic achievement in literacy and mathematics for students. On the other hand, increased vehicle emissions have a negative impact on academic performance. Vehicle emissions partially mediate the relationship between vegetation and academic performance.
ENVIRONMENTAL RESEARCH
(2022)
Article
Environmental Sciences
Narmilan Amarasingam, Felipe Gonzalez, Arachchige Surantha Ashan Salgadoe, Juan Sandino, Kevin Powell
Summary: This study used unmanned aerial vehicles (UAVs) and deep learning (DL) techniques to detect white leaf disease (WLD) in sugarcane fields in Sri Lanka. The performance of different DL models was evaluated and YOLOv5 was recommended as the best model for WLD detection. The proposed methodology provides technical guidelines for accurate detection and treatment of WLD.
Article
Environmental Sciences
Narmilan Amarasingam, Mark Hamilton, Jane E. Kelly, Lihong Zheng, Juan Sandino, Felipe Gonzalez, Remy L. Dehaan, Hillary Cherry
Summary: This study explores the potential of machine learning algorithms to detect mouse-ear hawkweed foliage and flowers from UAV-acquired multispectral images. The analysis of imagery obtained from a highly infested study site in New Zealand revealed that a spatial resolution of 0.65 cm/pixel achieved the highest detection and validation accuracy. This methodology can optimize the use of UAV remote sensing technologies for better resource allocation.
Article
Environmental Sciences
Violet Walker, Fernando Vanegas, Felipe Gonzalez
Summary: This work proposes a modeling approach and software framework for coordinating multiple UAVs in large, complex, and partially observable environments for target finding or surveying points of interest. The framework includes mapping and path-solving using an extended NanoMap library, solving the global planning problem using an online model-based solver, and solving the local control problem using deep reinforcement learning. Simulated testing shows that the proposed framework enables multiple UAVs to search and target-find within large, complex, and partially observable environments.
Article
Remote Sensing
Dipraj Debnath, Ahmad Faizul Hawary, Muhammad Iftishah Ramdan, Fernando Vanegas Alvarez, Felipe Gonzalez
Summary: This paper presents QuickNav, a solution for obstacle detection and avoidance in unmanned aerial systems (UASs)/drones. QuickNav uses a geometrical approach and a predefined safe perimeter to estimate intercepting points and generate avoiding waypoints, resulting in shorter distances and time compared to other methods. The algorithm can be easily translated into different programming languages.
Article
Remote Sensing
Amarasingam Narmilan, Felipe Gonzalez, Arachchige Surantha Ashan Salgadoe, Kevin Powell
Summary: This study presents an initial detection method for sugarcane white leaf disease using high-resolution multispectral sensors mounted on unmanned aerial vehicles (UAVs) and supervised machine learning classifiers. The results show that this technology provides a reliable and quick method for detecting white leaf disease, with significant practical applications.
Article
Biochemistry & Molecular Biology
Farida Abubakari, Denise R. Fernando, Philip Nti Nkrumah, Hugh H. Harris, Peter D. Erskine, Antony van der Ent
Summary: Macadamia integrifolia and M. tetraphylla, unlike M. ternifolia, are known for their edible nuts. This study investigates the distribution of manganese (Mn) and other plant nutrients in the tissues and cells of these three Macadamia species. The results show that Mn is primarily sequestered in the leaf and midrib palisade mesophyll cells of all three species, with Mn also present in leaf interveinal regions, root cortical cells, and phloem cells. The study provides new insights into Mn compartmentalization in these highly Mn-tolerant Macadamias and expands knowledge about the potentially toxic over-accumulation of an essential micronutrient, which can inform farming strategies for edible species.
