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2023 International Conference on robotics and automation in Industry, ICRAI 2023

作者： Mohiz, Abdul Nasir, Fazal E. Shah, Kamran University of Engineering & Technology Department of Mechatronics Engineering Peshawar Pakistan Advanced Robotics & Automation Lab National Center of Robotics & Automation Peshawar Pakistan

ISBN: (纸本)9781665464727

Tillage of the soil is the most important consideration when it comes to the implementation of agricultural practices. Increases in crop yield has been achieved through a variety of agricultural practices thanks to the discoveries of various agricultural experts. The planting process is the one that has the greatest impact on the crop's overall health. The hull can be more precisely prepared for the seed-planting trench with the assistance of furrows. A variety of furrow openers are currently undergoing the implantation process. Studying dynamic systems that are discontinuous in nature can be done with the help of discrete element modelling. The simulation of a tine-shaped furrow opener using the EDEM package software was carried out for three different speeds. When the speed of an object increases, so does the force it exerts on it. Additionally, the length of an object has an effect on the force it exerts. Additionally, taken into consideration were the profiles that were generated in the soil. To carry out statistical validation of the results analysis of variation (ANOVA) was done. The results provided a basis for calculating a confidence level of 95%. For the furrow openers, it was suggested that a speed of 0.495 meters per second, which is equivalent to 1.76 kilometers per hour, be used. © 2023 IEEE.

关键词： Tillage

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Control Simulation of Proportional-Integral and Sliding Mode Control for Precision Seed Planters

Control Simulation of Proportional-Integral and Sliding Mode...

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2023 International Conference on robotics and automation in Industry, ICRAI 2023

作者： Nawaz, Yasir Qadir, Muhammad Usman Khan, Muhammad Awais Haq, Izhar Ul Shah, Kamran Khan, Tahir Advanced Robotics & Automation Lab Department of Mechatronics University of Engineering and Technology Peshawar Pakistan

ISBN: (纸本)9781665464727

The desired development and design of an electric control system (ECS) for a precision planter is one of the most crucial elements in evaluating the efficacy of applicators for plant production. The seeds would be sown using this approach. Years have been invested in the continuous development of a range of application methods and metering systems, each of which offers specific advantages for applying the required system with a high degree of precision. Researchers worldwide have been trying to make electric-driven seed meters (EDSM) for planters, but they haven't succeeded. This study looks into the current state of installing seed metering systems for precision planters. Proportional-integral (PI) and sliding mode control (SMC) designs of the control system have been implemented to improve the planting quality of the planters. We want to highlight the electrically driven control system (EDCS) using these designs. An overview of the noteworthy features and limitations of past research is given. We also discuss several future directions for future research, concentrating on the knowledge gaps in this area. © 2023 IEEE.

关键词： Sliding mode control

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Design and Implementation of Model Predictive Control (MPC) Based Pressure Regulation System for a Precision Agricultural Sprayer

Design and Implementation of Model Predictive Control (MPC) ...

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2023 International Conference on robotics and automation in Industry, ICRAI 2023

作者： Khan, Adrees Nasir, Fazal Tufail, Muhammad Haris, Muhammad Khan, Muhammad Tahir Dong, Zhang University of Engineering and Technology Department of Mechatronics Engineering Peshawar Pakistan Advanced Robotics and Automation Lab National Center of Robotics and Automation Peshawar Pakistan Jinan China

ISBN: (纸本)9781665464727

Model Predictive Control (MPC) is a control scheme that involves predicting the future behavior of a system and optimizing control actions to accomplish the desired objective. In this study, we develop an intelligent control algorithm, based on MPC to regulate the target pressure in variable-rate agriculture sprayer robots. Modeling and simulation steps of the spraying system are developed using MATlab/Simulink environment, before passing to the description of the MPC algorithm. Real-time implementation of the MPC algorithm was conducted on an Arduino Mega 2560 controller board by using Simulink Support Package for Arduino Hardware in MATlab/Simulink to experimentally validate the preliminary results of simulations. The work evaluates MPC to regulate the pressure in the system and compares the results with a traditional PID control system. Moreover, MPC is a novel method for nonlinear system control that achieves zero steady-state error, low transient response, and reduces peak overshoot compared to the results obtained with a PID controller, thereby reducing the waste of chemicals, and minimizing the toxicology and environmental risk. © 2023 IEEE.

关键词： Model predictive control

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Real-Time Plant Recognition and Crop Row Navigation for Autonomous Precision Agricultural Sprayer Robot

Real-Time Plant Recognition and Crop Row Navigation for Auto...

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2023 International Conference on robotics and automation in Industry, ICRAI 2023

作者： Nasir, Fazal Haris, Muhammad Khan, Bilawal Tufail, Muhammad Khan, Muhammad Tahir Dong, Zhang National Center of Robotics and Automation Advanced Robotics and Automation Lab Peshawar Pakistan University of Engineering and Technology Department of Mechatronics Engineering Peshawar Pakistan Jinan China

ISBN: (纸本)9781665464727

This paper presents a vision-based selective spraying technique for an autonomous agricultural sprayer robot. In traditional methods, excessive chemical spraying cause deleterious effects on human health, environment and becomes uneconomical. In order to reduce the agrochemical wastage encounters in a broadcast spraying, a selective plant spraying method is used for crop chemical treatment. The sensor-based approach assisted with YOLOv7 model is deployed on a custom designed robot for recognizing and localizing the lettuce plants in field. The PID-based pressure controller is designed that minimizes the undesirable fluctuations cause by the opening/closing of solenoid-valve-nozzles (SVNs) during spraying. Thus the nozzle's spraying quality is maintained by keeping the pressure constant to a desired value. A visual servoing scheme for row tracking is presented that uses the detected plant's spatial features. The robustness of the visual-based navigation is validated in the real field experiments. © 2023 IEEE.

关键词： Crops

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Obstacle avoidance in human-robot cooperative transportation with force constraint

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Science China(Information Sciences) 2023年第1期66卷 334-335页

作者： Ying ZHANG Chenguang YANG Sheng XU Yongsheng OU College of Automation Science and Engineering South China University of Technology Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced TechnologyChinese Academy of Sciences

Dear editor,Robots are often conceived as human-like machines that can interact with humans naturally and safely. Human-robot interaction means that robots can communicate with people,understand their needs, and act accordingly [1]. This interaction is critical when two people are needed to finish a task cooperatively.

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Design and Development of IoT Based Weather and Air Quality Monitoring Station

Design and Development of IoT Based Weather and Air Quality ...

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2023 International Conference on robotics and automation in Industry, ICRAI 2023

作者： Haris, Muhammad Ubaid, Bilal Bibi, Uzma Said, Ameer Us Saqib, Syed Najm Khan, Shahbaz Tufail, Muhammad Advanced Robotics and Automation Lab National Center of Robotics and Automation Peshawar Pakistan University of Engineering and Technology Department of Mechatronics Engineering Peshawar Pakistan Institute of Manufacturing Engineering Management University of Engineering and Applied Sciences Swat Swat Pakistan

ISBN: (纸本)9781665464727

This paper presents the Design and Development of IoT Based Weather and Air Quality Monitoring stations that provide weather-related information for agriculture, and aviation climate forecasting purposes. The prototype is made up of an outdoor unit that consistently monitors numerous climatic variables such as temperature, humidity, barometric pressure, wind speed, wind direction, rainfall, and air quality using sensors with high accuracy. The air quality index(AQI) is also calculated using the sensors values which tell us whether the atmosphere is safe or polluted. ESP32(Microcontroller) which has a WiFi module is used to gather and send the sensor data through the Internet of things (IoT) to a ThingSpeak channel (IoT cloud), an internet platform where the data is saved, analyzed and read the data remotely. The weather station makes use of photovoltaic power and a rechargeable lead-acid battery to sustain the system. This paper also discusses the obvious strengths and shortcomings of the system and suggests plausible upgrades to assist the system in obtaining higher and long-term performance. © 2023 IEEE.

关键词： Internet of things

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Step-by-step Linearized Kalman Filter-Based Fault Detection of Workpiece Machining

Step-by-step Linearized Kalman Filter-Based Fault Detection ...

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2023 CAA Symposium on Fault Detection, Supervision and Safety for Technical Processes, SAFEPROCESS 2023

作者： Sun, Xiaohui Wu, Xinyu Wen, Chenglin Ma, Xue Tsinghua University Department of Automation Beijing China Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Shenzhen China Guangdong University of Petrochemical Technology School of Automation Maoming China

ISBN: (纸本)9798350337754

This paper is concerned with step-by-step linearized Kalman filter to deal with multiplicative faults diagnosis problem for class of nonlinear systems. Multiplicative fault variables are defined as parameter variables to be estimated, and linear dynamic models between fault variables and all variables are established. The indirect linear state and measurement models of fault variables and the corresponding step-by-step linearized Kalman filters are established based on current estimated values of all variable and some obtained estimated values of future variables;further, combined with fault variables, a filter is designed for state variables in the linearized system. On basis of EKF, the redisual generation is obtained. The effectiveness of the novel filter is verified in workpiece machining process. © 2023 IEEE.

关键词： Fault detection

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Small Sample Learning Mechanism Based on Knowledge-transferring for Fault Diagnosis

Small Sample Learning Mechanism Based on Knowledge-transferr...

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2023 CAA Symposium on Fault Detection, Supervision and Safety for Technical Processes, SAFEPROCESS 2023

作者： Ma, Xue Wu, Xinyu Wen, Chenglin Sun, Xiaohui Tsinghua University Department of Automation Beijing China Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Shenzhen China Guangdong University of Petrochemical Technology Department of Automation Maoming China

ISBN: (纸本)9798350337754

Deep learning-based methods have been applied in many fields which has received increased attention. It requires large annotated data to train a deep model with good generalization ability. However, it may be very difficult, time-consuming, and even expensive to collect and annotate practical industrial data, for example, for fault diagnosis in industrial systems. To address this issue, a novel small sample learning (SSL) mechanism based on Knowledge-transferring is proposed in this manuscript, which leverages the expert system and deep neural network simultaneously. Firstly, an annotator is constructed based on a belief rule base (BRB) expert system only with available small labeled samples. Then, the left unlabeled samples will be labeled through the annotator to form an augmented training dataset (ATD) with the available small labeled samples, which can realize the data representation of expert knowledge. Besides, a united optimization model based on CNN that combines data and knowledge is built, which has realized the transfer of expert knowledge. Finally, we demonstrate the capability of the proposed method on the dataset collected from the real experimental platform for rotating machinery fault diagnosis. © 2023 IEEE.

关键词： Failure analysis

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Effect of Tine Shaped Furrow Opener on Dry Soil Using Discrete Element Modelling

Effect of Tine Shaped Furrow Opener on Dry Soil Using Discre...

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International Conference on robotics and Artificial Intelligence (ICRAI)

作者： Abdul Mohiz Fazal E Nasir Kamran Shah Department of Mechatronics Engineering University of Engineering & Technology Peshawar Pakistan Advanced Robotics & Automation Lab National Center of Robotics & Automation Peshawar Pakistan

关键词： Meters Industries automation Force Crops Soil Software

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An Autoencoder-Based Feature Extraction Method Applied to the Detection of Lateral Walking Gait Phase 1

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16th International Conference on Intelligent robotics and Applications, ICIRA 2023

作者： Yang, Lijun Xiang, Kui Pang, Muye Luo, Mingxiang Yin, Meng Li, Wenju Cao, Wujing School of Automation Wuhan University of Technology Wuhan430070 China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518005 China

ISBN: (数字)9789819964987

ISBN: (纸本)9789819964970

The traditional method of extracting time-domain features is subjective and cumbersome. An autoencoder-based feature extraction method is proposed to overcome these shortcomings. Experiments were conducted to detect gait phases of lateral walking of 10 subjects at various gait cycles (rhythms) and strides, which combined into 9 lateral walking modes. Based on the stacked autoencoder with dropout (AE-dropout), different quantities of features from the original data were extracted. Subsequently, these features were used to detect the phase of lateral walking gait based on decision tree (Tree), k-Nearest Neighbors (KNN), support sector machines (SVM), and artificial neural network (ANN). The results demonstrated that the KNN, SVM, and ANN achieve higher accuracy after using the features extracted by our method for the detection of lateral walking gait phase. Moreover, with the increase of the number of extracted features, the cross-subject accuracy of the four models (AE-dropout + X, X represents Tree, KNN, SVM, and ANN) exhibit similar regularities, which increased first and then decreased. In addition, compared to the method of extracting time-domain features, our method has a smaller standard error of mean (SEM) in cross-subject recognition accuracy for different lateral walking modes. It proves that our method has greater generalization capabilities. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Feature extraction

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