Article
Computer Science, Information Systems
Youyoung Yang, Henzeh Leeghim, Donghoon Kim
Summary: This study proposes a Dubins path-oriented RRT* algorithm for unmanned aerial vehicles (UAVs) path generation. The algorithm considers the flight direction and minimum radius of rotation, improving optimality and convergence. Compared to existing algorithms, the proposed algorithm shows significant improvements in path length and computation time.
Article
Engineering, Marine
Di Lu, Chengke Xiong, Hexiong Zhou, Chenxin Lyu, Rui Hu, Caoyang Yu, Zheng Zeng, Lian Lian
Summary: The study introduces an improved design of a multimodal hybrid aerial underwater vehicle capable of level and vertical flight, hovering, and underwater glide. The innovation lies in the novel configuration and lightweight pneumatic buoyancy system to balance flight payload and underwater weight. The prototype, named Nezha III, demonstrates excellent performance in different modes and remarkable capability of diving to 50 meters depth.
Article
Horticulture
Ye-Seong Kang, Ki-Su Park, Eun-Ri Kim, Jong-Chan Jeong, Chan-Seok Ryu
Summary: In this study, hyperspectral imaging from an unmanned aerial vehicle was used to estimate the TNC concentration in apple trees. The results can provide useful information for precise nutrient management to improve the yield and quality of apple trees, when combined with previous studies on estimating the nitrogen concentration.
Article
Robotics
Chenxin Lyu, Di Lu, Chengke Xiong, Rui Hu, Yufei Jin, Jianhu Wang, Zheng Zeng, Lian Lian
Summary: This research presents the design and testing of a novel hybrid aerial underwater vehicle (HAUV) called Nezha III. It features a piston-driven underwater glide strategy and combines the characteristics of an underwater glider and a fixed-wing vertical takeoff and landing aircraft. The vehicle prototype was built and field experiments were conducted to evaluate its performance. The experiment results show that Nezha III has extended underwater endurance and operational depth compared to existing HAUVs.
JOURNAL OF FIELD ROBOTICS
(2022)
Article
Remote Sensing
Wenli Zhang, Xinyu Peng, Guoqiang Cui, Haozhou Wang, Daisuke Takata, Wei Guo
Summary: This paper proposes a skeleton extraction algorithm for sparse point clouds generated by UAV RGB images, and evaluates the algorithm's performance using three metrics: F1-score of bifurcation point (FBP), F1-score of end point (FEP), and Hausdorff distance (HD). The results show that the algorithm performs well in extracting the main skeleton from the sparse fruit tree branch point cloud. It has practical application value in the management of orchards.
Article
Environmental Sciences
Pan Zhou, Zhibin Sun, Xiongqing Zhang, Yixiang Wang
Summary: This study provides a novel framework for planning thinning operations in a pure managed forest using Unmanned Aerial Vehicle (UAV) remote sensing techniques. The framework allows obtaining forest attributes and optimizing thinning areas, intensities, and cut-trees. Results from a case study in a subtropical Chinese fir plantation show the potential of low-cost UAV-acquired RGB images in depicting forest structure.
SCIENCE OF THE TOTAL ENVIRONMENT
(2023)
Article
Multidisciplinary Sciences
Ranjan Sapkota, John Stenger, Michael Ostlie, Paulo Flores
Summary: Currently, the most common method of controlling weeds in commercial agricultural production system is by applying uniform distribution of chemical herbicide through a sprayer without considering the spatial distribution information of crops and weeds, resulting in excessive chemical herbicides being applied. This study aimed to implement site-specific weed control (SSWC) in a corn field by using unmanned aerial system (UAS) to map the spatial distribution of weeds, creating a prescription map based on the weed distribution map, and spraying the field using the prescription map. With our SSWC approach, we were able to save 26.2% of the acreage from being sprayed with herbicide compared to the current method.
SCIENTIFIC REPORTS
(2023)
Article
Computer Science, Artificial Intelligence
Anthony Wagner, John Peterson, James Donnelly, Shivam Chourey, Kevin Kochersberger
Summary: This paper discusses a collaborative air-ground team of autonomous vehicles for exploring and navigating outdoors within an unknown environment. By using a custom multi-rotor equipped with onboard downward facing stereo cameras to capture imagery and reconstruct a height map of the ground surface online, and combining it with a simple terrain classifier, obstacles can be detected and navigation costs can be estimated. Through an online exploration algorithm, the team is able to discover a path for the ground vehicle from the current position to the goal and make progress with partial paths before a complete path is found.
JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
Jiaxin Chen, Qihui Wu, Yuhua Xu, Nan Qi, Xin Guan, Yuli Zhang, Zhen Xue
Summary: This paper proposes a cooperative reconnaissance and spectrum access scheme for task-driven heterogeneous coalition-based UAV networks by jointly optimizing task layer and resource layer. The effectiveness of the proposed scheme and algorithms is demonstrated through in-depth numerical simulations, showing superiority over non-joint optimization schemes. Additionally, the proposed coalition expected altruistic order is shown to be superior to traditional Pareto order and selfish order.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
(2021)
Article
Agronomy
Juan Manuel Ponce, Arturo Aquino, Diego Tejada, Basil Mohammed Al-Hadithi, Jose Manuel Andujar
Summary: This paper describes a methodology for the automated detection and delineation of tree crowns in aerial images of crop fields. The method shows promising results in accurately estimating plant population and canopy coverage in intensive tree-based orchards, providing valuable information for farmers.
Article
Chemistry, Physical
Emre Ozbek, Gorkem Yalin, Mustafa Umut Karaoglan, Selcuk Ekici, C. Ozgur Colpan, T. Hikmet Karakoc
Summary: The study focuses on developing a PEM fuel cell Li Po battery hybrid system to increase flight endurance, with the evaluation and testing based on experimental power demand data. It was found that the fuel cell could meet most of the power demand, indicating its potential for improving UAV flight capabilities.
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
(2021)
Article
Automation & Control Systems
Xinyu Cai, Shane Kyi Hla Win, Hitesh Bhardwaj, Shaohui Foong
Summary: In this study, a novel modular aerial robotic platform called ARROWs is introduced, which can be easily reconfigured with customized wing and control modules. Unlike conventional multirotor aerial vehicles, ARROWs generate more lift through revolving wings. However, the complex dynamics pose challenges in flight controller development. To address this, a cascaded flight controller is designed based on simplified flight dynamics and relaxed hovering conditions, while inertial measurement units are employed to estimate flight configuration. Experimental results validate the proposed platform and flight control strategy in 12 different configurations.
IEEE-ASME TRANSACTIONS ON MECHATRONICS
(2023)
Article
Computer Science, Interdisciplinary Applications
Jun Guo, Wei Xia, Xiaoxuan Hu, Huawei Ma
Summary: In this study, a data-driven approach is proposed for unmanned aerial vehicle (UAV) path planning in a hostile environment. The feedback rapidly-exploring random tree star algorithm (FRRT*) is used, along with a data-driven risk network and feedback module, to improve planning efficiency.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Robotics
Zhefan Xu, Di Deng, Kenji Shimada
Summary: The proposed dynamic exploration planner (DEP) utilizes incremental sampling and Probabilistic Roadmap (PRM) to explore unknown environments, demonstrating successful exploration in dynamic environments while outperforming benchmark planners in terms of exploration time, path length, and computational time.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2021)
Article
Computer Science, Information Systems
Jong Wan Seo, Anik Islam, Md Masuduzzaman, Soo Young Shin
Summary: This paper proposes a blockchain-based firmware update method using unmanned aerial vehicles (UAVs) to solve the firmware security problem in the IoT environment. It utilizes private blockchains for high scalability and transaction speed, and overcomes internet connection limitations by utilizing UAVs for firmware updates. The proposed method securely manages IoT device and firmware information through participant registration, firmware registration/update, firmware update request, and firmware update. Security analysis based on the STRIDE model and simulation on Hyperledger are conducted to prove the security and performance of the proposed method.
Article
Engineering, Electrical & Electronic
Christopher H. Betters, Joss Bland-Hawthorn, Salah Sukkarieh, Itandehui Gris-Sanchez, Sergio G. Leon-Saval
IEEE PHOTONICS TECHNOLOGY LETTERS
(2020)
Article
Automation & Control Systems
Jasper Brown, Daobilige Sua, He Kong, Salah Sukkarieh, Eric Kerrigan
Article
Automation & Control Systems
He Kong, Mao Shan, Daobilige Su, Yongliang Qiao, Abdullah Al-Azzawi, Salah Sukkarieh
Article
Robotics
Jasper Brown, Salah Sukkarieh
Summary: The study presents a modifiable development platform for robotic fruit harvesting, which was evaluated in a commercial plum orchard. New technologies such as soft robotics and persistent target tracking significantly improve performance, but moving to new fruit types still presents challenges.
JOURNAL OF FIELD ROBOTICS
(2021)
Article
Agricultural Engineering
Daobilige Su, Yongliang Qiao, He Kong, Salah Sukkarieh
Summary: The study presents a deep neural network method for real-time segmentation of inter-row ryegrass weeds in wheat fields, showing the best segmentation performance among various popular algorithms on a wheat farm dataset. The proposed method utilizes two subnets to enhance segmentation accuracy and achieves a real-time processing speed of 48.95 FPS.
BIOSYSTEMS ENGINEERING
(2021)
Review
Agriculture, Multidisciplinary
Yongliang Qiao, He Kong, Cameron Clark, Sabrina Lomax, Daobilige Su, Stuart Eiffert, Salah Sukkarieh
Summary: Precision livestock farming, utilizing intelligent perception tools, can analyze individual animals for improved management and increased farm productivity. The focus is on techniques related to identification, body condition score evaluation, and live weight estimation, with over 100 relevant papers reviewed and discussed for insights into future developments in non-contact, high precision, automated technologies in the field.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2021)
Article
Automation & Control Systems
He Kong, Mao Shan, Salah Sukkarieh, Tianshi Chen, Wei Xing Zheng
Summary: Recent progress has been made in Kalman filter (KF) with norm constraints on the state due to its potential applications in robotics and navigation. A noticeable discovery is that the KF gain has an analytical expression and the brute-force normalization is optimal in the mean-square sense. However, existing results are limited to cases where models/bounds or statistical properties of the disturbances are known.
Article
Agriculture, Multidisciplinary
Jasper Brown, Yongliang Qiao, Cameron Clark, Sabrina Lomax, Khalid Rafique, Salah Sukkarieh
Summary: Knowing where livestock are located enables optimized management and mustering. However, many of Australia's livestock are unmonitored due to the large size of farms, impacting farm profit, animal welfare, and the environment. This study explores the association between object detector performance and spatial degradation for cattle, sheep, and dogs, using simulated point spread functions and various optical qualities. The findings inform the selection of remote sensing data requirements for animal detection tasks, allowing farmers and ecologists to use more accessible medium-resolution imagery confidently.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2022)
Article
Agriculture, Multidisciplinary
Daobilige Su, He Kong, Yongliang Qiao, Salah Sukkarieh
Summary: This paper discusses a new method based on data augmentation, which improves the performance of deep learning networks for crops and weeds classification in agricultural robotics by enhancing the original image cropping and patching method. Experimental results show that the proposed framework can effectively enhance segmentation accuracy on datasets from different farms.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2021)
Article
Robotics
Daobilige Su, He Kong, Salah Sukkarieh, Shoudong Huang
Summary: This article discusses the importance of sensor array-based systems in robotic applications, focusing on calibration and sound source localization of microphone arrays. By using the Fisher information matrix approach, necessary and sufficient conditions for parameter identifiability are proposed, with thorough discussions on the three-dimensional case. The tools and concepts presented in this article can also be applied to other TDOA sensing modalities such as ultrawide band (UWB) sensors.
IEEE TRANSACTIONS ON ROBOTICS
(2021)
Review
Agriculture, Dairy & Animal Science
Yongliang Qiao, He Kong, Cameron Clark, Sabrina Lomax, Daobilige Su, Stuart Eiffert, Salah Sukkarieh
Summary: Cattle lameness detection and behavior recognition are key objectives in precision livestock farming (PLF), with advancements in smart sensors, big data, and artificial intelligence providing automatic tools. The review discusses over 100 papers on automated techniques for detecting cattle lameness and recognizing animal behaviors, highlighting the need for further research to enhance data quality and modeling accuracy. The study anticipates that intelligent perception for cattle behavior and welfare monitoring will develop towards standardization, scalability, and intelligence in conjunction with Internet of things (IoT) and deep learning technologies, with key challenges and opportunities emphasized for future research.
Article
Automation & Control Systems
Tengfei Xue, Yongliang Qiao, He Kong, Daobilige Su, Shirui Pan, Khalid Rafique, Salah Sukkarieh
Summary: This article proposes a one-shot learning-based approach for segmenting animal videos using only one labeled frame. The approach consists of three main modules: guidance frame selection, Xception-based fully convolutional network, and postprocessing. Experimental results show that the proposed approach achieves good performance on the DAVIS 2016 animal dataset and outperforms state-of-the-art methods.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Automation & Control Systems
He Kong, Salah Sukkarieh, Travis J. Arnold, Tianshi Chen, Wei Xing Zheng
Summary: This paper investigates the identifiability of noise covariances in linear Gaussian systems with arbitrary unknown inputs using the correlation-based autocovariance least-squares approach. The results show that the process noise covariance and the measurement noise covariance cannot be jointly identified uniquely, and neither of them can be uniquely identified when the other is known. This study provides valuable insights into the applicability of existing filtering frameworks and calls for further research on alternative noise covariance methods under unknown inputs.
SYSTEMS & CONTROL LETTERS
(2022)
Proceedings Paper
Automation & Control Systems
Jennifer Wakulicz, He Kong, Salah Sukkarieh
Summary: This paper discusses the scenario where the dynamic model of the target is subject to arbitrary unknown inputs in real-world situations, and proposes a solution to the sensor trajectory planning problem. By using an unknown input decoupled filter to track the target state and applying concepts of Reduced Value Iteration, a suboptimal solution with performance guarantees for tracking both the state and the unknown input is presented.
2021 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA 2021)
(2021)
Article
Agricultural Engineering
Yangyang Guo, Yongliang Qiao, Salah Sukkarieh, Lilong Chai, Dongjian He
Summary: The proposed BiGRU-attention method based on deep learning can significantly improve animal behavior classification accuracy and achieved good performance in experiments.
TRANSACTIONS OF THE ASABE
(2021)
Article
Robotics
Aime Charles Alfred Dione, Shoichi Hasegawa
Summary: This study proposes a new method to solve the kinematic hyper redundancy problem in posture control of a robotic arm with redundant degrees of freedom. By controlling strategic points along the arm, the method guides the overall motion of the arm towards the target posture. The method is capable of safely and accurately tracking target postures that are significantly different from the initial posture.
Article
Robotics
Peirang Li, Naoya Ueda, Chi Zhu
Summary: This study focuses on the traditional attendant-propelled power-assist wheelchairs (APAWs) and identifies the discomfort caused by changes in handle velocity when passing through a slope. To address this issue, a velocity compensation method is proposed and validated through simulations and experiments.
Article
Robotics
Juan Padron, Kenta Tatsuda, Kiyoshi Ohishi, Yuki Yokokura, Toshimasa Miyazaki
Summary: This paper proposes a method that takes into account real-time posture-dependent inertial variation to achieve exact dynamic compensation and independent control of each axis for industrial robots. By discretizing the state equations of the posture-variant two-inertia system model, the whole control system can be easily redeisgned at each control cycle to address the issues caused by posture changes.