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RSI/ISM International Conference on Robotics and Mechatronics (ICROM)

作者： Arshia Rezaei Erfan Radfar Amin Talaeizadeh Aria Alasty Department of Mechanical Engineering Advanced Research Lab for Control and Agricultural Robotics (Sharif AgRoLab) Sharif University of Technology

ISBN: (数字)9798331529734

ISBN: (纸本)9798331529741

Multirotor Unmanned Aerial Vehicles (UAV)s flight performance rely on accurate estimation of their attitude and position for stable and robust control, which is essential for precise path following and management. Traditional methods for estimating six Degrees of Freedom (DoF) parameters, such as position, orientation, and velocity, often combine data from Global Navigation Satellite System (GNSS), Inertial Measurement Unit (IMU), and vision sensors using complex algorithms for fusion and filtering. This approach can lead to challenges in real-time processing and robustness to environmental variations. In this paper, we propose a novel approach that leverages deep learning and incorporates a physics-informed loss function based on monocular vision data to enhance the accuracy of these sensors by eliciting position and heading data from a trained model of flow detection, enhanced with a mathematical model of optical flow. We implement a fusion of camera, IMU, magnetometer, and ultrasonic sensors for robust and accurate 6 DoF data acquisition in multirotor systems. Our proposed framework utilizes Convolutional Neural Networks (CNN)s to directly learn the mapping between sensor data and 6 DoF parameters. By jointly processing visual and inertial data in an end-to-end manner, our model exploits the complementary information provided by each sensor modality, thereby enhancing estimation accuracy and robustness to external disturbances. We demonstrate the effectiveness of our approach through extensive experiments on real-world multirotor platforms, show-casing significant improvements in pose and motion estimation accuracy compared to conventional methods. Our fusion deep learning framework offers a promising pathway for enhancing the autonomy and performance of multi rotor UAVs.

关键词： Deep learning Accuracy Measurement units Magnetic sensors Motion estimation Estimation Autonomous aerial vehicles Robot sensing systems Robustness Real-time systems

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Comparing the Performance of Quaternion, Rotation Matrix, and Euler Angles Based Attitude PID controllers for Quadrotors

Comparing the Performance of Quaternion, Rotation Matrix, an...

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RSI/ISM International Conference on Robotics and Mechatronics (ICROM)

作者： Arshia Rezaei Amin Talaeizadeh Aria Alasty Department of Mechanical Engineering Advanced Research Lab for Control and Agricultural Robotics (Sharif AgRoLab) Sharif University of Technology

ISBN: (数字)9798331529734

ISBN: (纸本)9798331529741

Attitude states are critical parameters in the control, navigation, and guidance of aerial robotics. Various models, including Euler angles, rotation matrices, and quaternions, are used to represent the orientation of multirotors. The performance of a quadrotor's attitude controller is significantly influenced not only by optimal gain design but also by the structure and strategy of error allocation and control command management. Given the dynamic behavior of the quadrotor, challenges arise with the Proportional-Integral-Derivative (PID) controller, which, as a Single Input Single Output (SISO) controller, struggles to manage the system's channels independently. This paper presents three attitude control strategies for a quadrotor, focusing on both controller design and state estimation by utilizing three-dimensional spatial rotation models. The aim is to compare and improve quadrotor attitude control strategies by applying diverse criteria through these spatial rotation models. The models are implemented on a 3 Degrees of Freedom (DoF) quadrotor stand. The comparison evaluates tracking error, energy consumption, computational effort, and other key performance metrics.

关键词： Solid modeling Attitude control Quaternions Computational modeling 3-DOF Stability criteria Resource management State estimation Robots Quadrotors

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Combined Photoredox Catalysis for Value-Added Conversion of Contaminants at Spatially Separated Dual Active Sites

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Research 2023年第3期6卷 597-607页

作者： Jieyuan Li Ruimin Chen Kaiwen Wang Yan Yang Jielin Wang Weiping Yang Shengyao Wang Guidong Yang Fan Dong Research Center for Carbon-Neutral Environmental and Energy Technology Institute of Fundamental and Frontier SciencesUniversity of Electronic Science and Technology of ChinaChengdu 611731China Beijing Key Lab of Microstructure and Properties of Advanced Materials Beijing University of TechnologyBeijing 100124China School of Environmental Science and Engineering Institute of Environmental Health and Pollution ControlGuangdong University of TechnologyGuangzhou 510006GuangdongChina College of Science Huazhong Agricultural UniversityWuhan 430070China XJTU-Oxford Joint International Research Laboratory of Catalysis School of Chemical Engineering and TechnologyXi’an Jiaotong UniversityXi’an 710049China

As 2 indispensable counterparts in one catalysis system,the independent reduction and oxidation reactions require synergetic regulation for cooperatively promoting redox *** the current success in promoting the catalytic efficiency of half reduction or oxidation reactions,the lack of redox integration leads to low energy efficiency and unsatisfied catalytic ***,we exploit an emerging photoredox catalysis system by combining the reactions of nitrate reduction for ammonia synthesis and formaldehyde oxidation for formic acid production,in which superior photoredox efficiency is achieved on the spatially separated dual active sites of Ba single atoms and Ti^(3+).High catalytic redox rates are accomplished for respective ammonia synthesis(31.99±0.79 mmol gcat^(−1) h^(−1))and formic acid production(54.11±1.12 mmol gcat^(−1) h^(−1)),reaching a photoredox apparent quantum efficiency of 10.3%.Then,the critical roles of the spatially separated dual active sites are revealed,where Ba single atoms as the oxidation site using h+and Ti3+as the reduction site using e−are identified,*** efficient photoredox conversion of contaminants is accomplished with environmental importance and competitive economic *** study also represents a new opportunity to upgrade the conventional half photocatalysis into the complete paradigm for sustainable solar energy utilization.

关键词： redox catalysis accomplished

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Grain size control in quasi-two-dimensional perovskite thin film via intermediate phase engineering for efficient bound exciton generation

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Science China Materials 2024年第12期67卷 3925-3931页

作者： Guohui Li Wenhui Zhao Kai Lin Kefan Zhao Yujing Wang Aohua Niu Rong Weng Kaibo Zheng Yanxia Cui College of Electronic Information and Optical Engineering Key Laboratory of Interface Science and Engineering in Advanced MaterialsKey Lab of Advanced Transducers and Intelligent Control System of Ministry of EducationTaiyuan University of TechnologyTaiyuan 030024China Chemical Physics Division and NanoLund Lund UniversityBox 12422100LundSweden

Quasi-two dimensional(2D)perovskites have emerged as a promising class of materials due to their remarkable photoluminescence efficiency,which stems from their exceptionally high exciton binding *** spatial confinement of excitons within smaller grain sizes could enhance the formation of biexcitons leading to higher radiative recombination ***,the synthesis of high-quality quasi-2D perovskite thin films with controllable grain sizes remains a challenging *** this study,we present a facile method for achieving quasi-2D perovskite thin films with controllable grain sizes ranging from 500 to 900 *** is accomplished by intermediate phase engineering during the film fabrication *** results demonstrate that quasi-2D perovskite films with smaller grain sizes exhibit more efficient bound exciton generation and a reduced stimulated emission threshold down to 15.89µJ cm^(−2).Furthermore,femtosecond transient absorption measurements reveal that the decay time of bound excitons is shorter in quasi-2D perovskites with smaller grain sizes compared to that of those with larger grains at the same pump density,which is 230.5 *** observation suggests a more efficient exciton recombination process in the smaller grain size *** findings would offer a promising approach for the development of efficient bound exciton lasers.

关键词： quasi-2D perovskite intermediate phase engineering bound exciton generation grain size control

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3D printed-electrospun PCL/hydroxyapatite/MWCNTs scaffolds for the repair of subchondral bone

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Regenerative Biomaterials 2023年第1期10卷 294-305页

作者： Yanyan Cao Lei Sun Zixian Liu Zhizhong Shen Wendan Jia Peiyi Hou Shengbo Sang College of Information Science and Engineering Hebei North UniversityZhangjiakou 075000China Shanxi Key Laboratory of Micro Nano Sensors&Artificial Intelligence Perception College of Information and ComputerTaiyuan University of TechnologyTaiyuan 030024China Key Lab of Advanced Transducers and Intelligent Control System of the Ministry of Education Taiyuan University of TechnologyTaiyuan 030024China Shanxi Research Institute of 6D Artificial Intelligence Biomedical Science Taiyuan 030031China

Osteochondral defect caused by trauma or osteoarthritis exhibits a major challenge in clinical treatment with limited symptomatic effects at *** regeneration and remodeling of subchondral bone play a positive effect on cartilage regeneration and further promotes the repair of osteochondral *** use of the strengths of each preparation method,the combination of 3D printing and electrospinning is a promising method for designing and constructing multi-scale scaffolds that mimic the complexity and hierarchical structure of subchondral bone at the microscale and nanoscale,*** this study,the 3D printed-electrospun poly(ɛ-caprolactone)/nano-hydroxyapatites/multi-walled carbon nanotubes(PCL/nHA/MWCNTs)scaffolds were successfully constructed by the combination of electrospinning and layer-by-layer 3D *** resulting dual-scale scaffold consisted of a dense layer of disordered nanospun fibers and a porous microscale 3D scaffold layer to support and promote the ingrowth of subchondral ***,the biomimetic PCL/nHA/MWCNTs scaffolds enhanced cell seeding efficiency and allowed for higher cell-cell interactions that supported the adhesion,proliferation,activity,morphology and subsequently improved the osteogenic differentiation of bone marrow mesenchymal stem cells in ***,this study elucidates that the construction of 3D printed-electrospun PCL/nHA/MWCNTs scaffolds provides an alternative strategy for the regeneration of subchondral bone and lays a foundation for subsequent in vivo studies.

关键词： additive manufacturing 3D printing electrospinning subchondral bone

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Advances and challenges of methanol-tolerant oxygen reduction reaction electrocatalysts for the direct methanol fuel cell

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Journal of Energy Chemistry 2023年第2期77卷 499-513,I0013页

作者： Muhammad Aizaz Ud Din Muhammad Idrees Sidra Jamil Syed Irfan Ghazanfar Nazir Muhammad Ahmad Mudassir Muhammad Shahrukh Saleem Saima Batool Nanpu Cheng Rahman Saidur School of Materials and Energy Southwest UniversityChongqing 400715China Additive Manufacturing Institute College of Mechatronics and Control EngineeringShenzhen UniversityShenzhen 518060GuangdongChina Chongqing Key Lab for Advanced Materials and Clean Energies of Technologies School of Materials and EnergySouthwest UniversityChongqing 400715China School of Materials Science and Engineering Dongguan University of TechnologyDongguan 523808GuangdongChina Department of Nanotechnology and Advanced Materials Engineering Sejong UniversitySeoul 05006Republic of Korea Department of Chemistry Khawaja Fareed University of Engineering and Information TechnologyRahim Yar Khan 64200Pakistan Laboratory for High Performance Ceramics EmpaSwiss Federal Laboratories for Materials Science and Technology8600 DübendorfSwitzerland Institute for Advanced Study Shenzhen UniversityShenzhen 518060GuangdongChina Research Centre for Nano-Materials and Energy Technology School of Engineering and TechnologySunway UniversityBandar SunwayMalaysia Department of Engineering Lancaster UniversityLancasterUnited Kingdom

Methanol cross-over effects from the anode to the cathode are important parameters for reducing catalytic performance in direct methanol fuel cells.A promising candidate catalyst for the cathode in direct methanol fuel cells must have excellent activity toward oxygen reduction reaction and resistance to methanol oxidation *** review focuses on the methanol tolerant noble metal-based electrocatalysts,including platinum and palladium-based alloys,noble metal–carbon based composites,transition metal-based catalysts,carbon-based metal catalysts,and metal-free *** understanding of the correlation between the activity and the synthesis method,electrolyte environment and stability issues are *** the transition metal-based catalyst,their activity,stability and methanol tolerance in direct methanol fuel cells and comparisons with those of platinum are particularly ***,strategies to enhance the methanol tolerance and hinder the generation of mixed potential in direct methanol fuel cells are also *** review provides a perspective for future developments for the scientist in selecting suitable methanol tolerate catalyst for oxygen reduction reaction and designing high-performance practical direct methanol fuel cells.

关键词： Oxygen reducing reaction Methanol tolerant electrocatalyst Portable power sources Direct methanol Fuel cell

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CBLN: A User Behavior Prediction Model Considering Content Correlation

CBLN: A User Behavior Prediction Model Considering Content C...

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2024 China Automation Congress, CAC 2024

作者： Deng, Yayin Liu, Xiaobo He, Lianyi Peng, Yongcheng Yu, Qizheng Wang, Shoucong School of Automation China University of Geosciences Wuhan430074 China Hubei Key Lab of Advanced Control and Intelligent Automation China University of Geosciences Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9798350368604

The core of user behavior prediction is Click-through Rate (CTR) prediction, which requires deep analysis of user actions such as clicks and browse. It is crucial to model user behavior sequences, content attributes, and user attributes to understand user preferences and improve CTR prediction accuracy. While many CTR prediction models are based on historical behavior sequences, most treat historical behavior representations merely as preferences, neglecting the representation of correlations between users and content. To address this, we propose a new model called the Correlated Behavior Learning Network (CBLN), for the task of user behavior prediction. This model includes a User Behavior Tracking Network (UBTN) and a Content Relevance Network (CRN), which dynamically modeling the evolution of user preferences related to target content and introduce content relevance to more comprehensively capture user behavior, thus more accurate predictions of user behavior can be made. We conducted extensive experiments on two public datasets to validate the effectiveness of our model, and the results showed that our proposed model achieved better performance than many complex CTR prediction models. © 2024 IEEE.

关键词： Prediction models

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Coverage Path Planning of Agricultural Spraying Drones with Graph Convolutional Network

Coverage Path Planning of Agricultural Spraying Drones with ...

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RSI/ISM International Conference on Robotics and Mechatronics (ICROM)

作者： Amirmasood Khaloujini Amin Talaeizadeh Alireza Taheri Aria Alastya Advanced Research Lab for Control and Agricultural Robotics Department of Mechanical Engineering Social and Cognitive Robotics Lab. Sharif University of Technology Tehran Iran

ISBN: (数字)9798331529734

ISBN: (纸本)9798331529741

Optimal route planning for autonomous robots is a crucial element of contemporary agriculture, especially for activities like spraying and pollination. This paper presents a Graph Convolutional Network (GCN) model especially developed to address the Coverage Path Planning (CPP). The aim of this paper is to convert the CPP problem into a Traveling Salesman Problem (TSP), so that by solving the TSP using the proposed neural network, an optimal route can be extracted for each agricultural field in the shortest possible time and with sufficient accuracy, ensuring full coverage of the field's area. The proposed model is a GCN, augmented with a transformer layer and a Multi-Layer Perceptron (MLP), was trained using datasets produced by a Genetic Algorithm (GA) Method. The model obtained a network error of 0.12 while solving TSP cases with 20 points. It showed robust generalization skills, as evidenced by validation and test errors of 0.1261 and 0.1264, respectively. Significantly, the GCN model reduces the solution time to approximately one-tenth compared to conventional approaches, a benefit that increases as the number of points increases. The effectiveness of the model in producing ideal coverage routes highlights its potential for wider use in optimization and coverage path planning, especially in dynamic and extensive agricultural environments.

关键词： Training Accuracy Graph convolutional networks Neural networks Spraying Traveling salesman problems Transformers Path planning Vehicle dynamics Genetic algorithms

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Self-Tuning PID controller for an Arm-Angle Adjustable Quadrotor Using an Actor-Critic-Based Neural Network

Self-Tuning PID Controller for an Arm-Angle Adjustable Quadr...

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Iranian Conference on Intelligent Systems (ICIS)

作者： Arshia Rezaei Amin Talaeizadeh Aria Alasty Department of Mechanical Engineering Advanced Research Lab for Control and Agricultural Robotics (Sharif AgRoLab) Sharif University of Technology Tehran Iran

ISBN: (数字)9798331507565

ISBN: (纸本)9798331507572

The increasing prevalence of multirotors necessitates the development of new configurations for specific applications. Innovative morphing of multirotors has enhanced their stability, maneuverability, agility, and overall performance. The utilization of Artificial Intelligence (AI) in robotics has enabled robots to exhibit autonomous behaviors in areas such as control, path planning, state estimation, system identification, and image processing. This paper introduces a novel approach to improving the control system of an adjustable arm-angle quadrotor through the integration of a self-tuning Proportional-Integral-Derivative (PID) controller, utilizing an Actor-Critic-based Neural Network (NN). Arm-angle adjustable quadrotors, with their complex and variable dynamics, present challenges in achieving optimal control performance across different arm angles. Traditional PID controllers often struggle to adapt efficiently to these dynamics. To address this issue, the Actor-Critic framework from reinforcement learning is employed to develop a self-tuning mechanism for the PID controller. The Actor network learns the optimal control actions, while the Critic network evaluates the performance of the control system, enabling continuous improvement. Extensive Software-in-the-Loop (SIL) and Hardware-in-the-Loop (HIL) tests demonstrate the effectiveness and feasibility of the proposed approach in achieving robust and adaptive control for tilt-arm quadrotors under diverse operating conditions. The results highlight the superiority of the Actor-Critic-based self-tuning PID controller over conventional methods, showcasing its potential for real-world devlopment in autonomous aerial systems.

关键词： Uncertainty Optimal control Reinforcement learning Artificial neural networks Autonomous aerial vehicles Real-time systems Adaptive control Robots Tuning Quadrotors

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Dynamic Modeling and Sliding Mode control of an Over-Actuated Quadrotor with Variable Hedral Angle of Propeller Axes

Dynamic Modeling and Sliding Mode Control of an Over-Actuate...

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International Conference on Unmanned Vehicle Systems-Oman (UVS)

作者： Ali Kafili Gavgani Amin Talaeizadeh Siamak Heidarzadeh Aria Alasty Hossein Nejat Pishkenari Department of Mechanical Engineering Advanced Research Lab for Control and Agricultural Robotics (Sharif AgRoLab) Sharif University of Technology Tehran Iran

The conventional quadrotor, characterized by four control inputs to control six degrees of freedom, is inherently under-actuated, resulting in limited independent control over pitch and roll angles. In this study, we present a configuration that incorporates four additional control inputs for manipulating the angles of the propeller axes. This addresses the previously mentioned limitations and offers additional advantages. Also, it can exhibit enhanced stability during altitude reduction by mitigating the vortex ring state. We derive the dynamic model for this system using Newthon-Euler's method. To address unmodeled dynamics, uncertainties, disturbances, and the inherent complexity of these systems, we utilize a nonlinear robust sliding mode controller. An affining process is performed to account for the non-affine nature of the dynamic equations. We introduce an optimization criteria aimed at maximizing battery life, leveraging the over-actuation of the system. This controller is applied to a dynamic system, infused with various uncertainties, such as inaccurate actuators, high-delayed servo motors, uncertain physical parameters, and wind disturbances. These factors collectively challenge the robustness of the control strategy. Additionally, the controller is implemented on a MATlab Simscape Multibody model. Given that the controller is model-based, the consistency of the obtained results validates the accuracy of the derived dynamic equations. This research aligns with the project SAC-1, one of the objectives of our lab, Sharif AgRolab.

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