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International Conference on robotics and Artificial Intelligence (ICRAI)

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

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.

关键词： Meters Industries PI control automation System performance Production Robustness

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Strictly Decentralized Approaches for Multi-Robot Grasp Coordination 19

Strictly Decentralized Approaches for Multi-Robot Grasp Coor...

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19th IEEE International Conference on automation Science and Engineering, CASE 2023

作者： Muthusamy, Rajkumar Kyrki, Ville Muthusamy, Praveen Kumar Taha, Tarek Hussain, Irfan Zweiri, Yahya Prattichizzo, Domenico Gan, Dongming Robotics Lab Dubai Future Labs Dubai United Arab Emirates Aalto University Intelligent Robotics Group Department of Electrical Engineering and Automation Finland Khalifa University of Science and Technology Abu Dhabi United Arab Emirates Istituto Italiano di Tecnologia Department of Advanced Robotics Genoa16163 Italy Purdue University United States

ISBN: (纸本)9798350320695

Grasp coordination is crucial for performing cooperative object manipulation tasks. Planning cooperative grasps among a group of decentralized robots is a new line of coordination problem that requires robots to simultaneously handle complex and large shaped and sized objects, a new level of difficulty that is rarely addressed in the literature. In this paper, we propose grasp coordination approaches for a decentralized group of robots facing explicit communication and sensing limitations. In particular, a scenario where robots with incomplete knowledge about each other's embodiments further lose the ability to 1. observe others' grasps occluded by the object's shape 2. exchange direct messages due to potential communication degradation resulting from the real-time planning and execution constraints. To tackle such a scenario, we introduce two baseline and two probabilistic approaches that are specifically designed for strict decentralization. The approaches analyze cooperative grasps using traditional grasp quality metrics and estimate cooperative grasps based on the assigned robot's priority. Simulation experiments demonstrate that the probabilistic approaches exhibit superior performance over the baseline approaches, reaching performance close to optimal for both homogeneous and heterogeneous groups. These approaches provide solutions to simulated multi-robot grasp coordination scenarios that have the potential to translate to real-world environments such as logistics, manufacturing, and services. © 2023 IEEE.

关键词： Industrial robots

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ViT-based Terrain Recognition System for wearable soft exosuit

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Biomimetic Intelligence & robotics 2023年第1期3卷 57-64页

作者： Fangliang Yang Chunjie Chen Zhuo Wang Hui Chen Yao Liu Gang Li Xinyu Wua Shenzhen Institute of Advanced Technology Chinese Academy of SciencesShenzhen 518055China Shenzhen College of Advanced Technology University of Chinese Academy of SciencesShenzhen 518055China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China Guangdong-Hong Kong-Macao Joint Laboratory of Human–Machine Intelligence-Synergy Systems Shenzhen 518055China SIASUN Robot and Automation CO. LtdShenyang 110169China

Terrain classification and force assistance strategies in complex environments have always piqued the interest of many *** wearable soft exosuits,inaccurate terrain recognition can easily introduce undesired assist forces that can easily injure the *** of these problems,we introduced a depth camera into the exosuit system,perform classification of terrain based on a Vision Transformer(ViT),and optimized the control algorithm,which is known as a ViT-Based Terrain Recognition System(TTRS).First,we used the Transformer algorithm to achieve a considerable classification effect in terrain *** also introduced terrain recognition as prior knowledge into the force assistance strategy of the exosuit,providing different force assistance to the exosuit in different ***,we performed human experiments with seven able-bodied people(six males and one female).The promising results demonstrate that our classification accuracy can reach 99.2%under six different terrains and that it can smoothly switch the force–assist curve in different terrains to better adapt to the complex terrain and improve the walking *** aforementioned terrain recognition algorithms and force–assist strategies may positively influence the study of soft exosuit,powered prostheses,and orthotics.

关键词： Vision Transformer(ViT) Depth camera Wearable soft exosuit Force assistance strategy Terrain recognition

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Diagnosis of Localized Bearing Defects using Texture Analysis of Vibration Envelope Signals and Machine Learning

Diagnosis of Localized Bearing Defects using Texture Analysi...

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

作者： Nguyen, Cong Dai Nasir, Fazal E. Khan, Shahbaz Khan, Sheraz Ali Kim, Jong-Myon Le Quy Don Technical University Faculty of Radio-Electronic Engineering Hanoi Viet Nam Advanced Robotics and Automation Lab National Center for Robotics and Automation Peshawar Pakistan Institute of Manufacturing University of Engineering and Applied Sciences Swat Pakistan University of Engineering and Technology Department of Mechatronics Engineering Peshawar Pakistan University of Ulsan Department of IT Convergence Ulsan Korea Republic of PD Technology Ulsan Korea Republic of

ISBN: (纸本)9781665464727

Bearings are important because they play a critical role in the operation of many machines and devices by reducing friction and enabling smooth motion between two moving parts. They are commonly used in rotating machinery, such as electric motors, turbines, pumps, and gearboxes, where they support and guide the rotating shafts. The primary cause of failure in wind turbines and induction motors is bearing faults, resulting in significant downtime and economic losses. Detecting these faults accurately and promptly is crucial to preventing unexpected shutdowns. Most of the existing methods for bearing fault detection rely on envelope analysis, which involves filtering and demodulating the raw signal, and Fourier analysis of the envelope signal to identify defect frequencies. Recent research has focused on improving the visibility of these frequencies by selecting an optimal band for filtering, using sub-band analysis and spectral kurtosis, which is a complex process and can be time-consuming. This paper presents a new approach to envelope signal analysis using texture analysis of the envelope signals that are projected as 2D grayscale images where each fault generates a unique texture. These textures are encoded using the local binary pattern operator and then used for fault classification. The method is tested on a publicly available seeded fault dataset. © 2023 IEEE.

关键词： Signal analysis

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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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International Conference on robotics and Artificial Intelligence (ICRAI)

作者： Fazal Nasir Muhammad Haris Bilawal Khan Muhammad Tufail Muhammad Tahir Khan Zhang Dong Advanced Robotics and Automation Lab National Center of Robotics and Automation Peshawar Pakistan Department of Mechatronics Engineering University of Engineering and Technology Peshawar Pakistan Institute of Automation Qilu University of Technology (Shandong Academy of Sciences) Jinan China

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.

关键词： Service robots Plants (biology) Spraying Crops Wheels Robot sensing systems Visual servoing

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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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International Conference on robotics and Artificial Intelligence (ICRAI)

作者： Adrees Khan Fazal Nasir Muhammad Tufail Muhammad Haris Muhammad Tahir Khan Zhang Dong Department of Mechatronics Engineering University of Engineering and Technology Peshawar Pakistan Advanced Robotics and Automation Lab National Center of Robotics and Automation Peshawar Pakistan Institute of Automation Qilu University of Technology (Shandong Academy of Sciences) Jinan China

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.

关键词： Transient response Toxicology Software packages Spraying Agriculture Regulation Real-time systems

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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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International Conference on robotics and Artificial Intelligence (ICRAI)

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

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.

关键词： Temperature sensors Cloud computing Wind speed Transportation Air quality Sensors Internet of Things

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A Real- Time Multi-Camera Auto-Adjustment Framework for Infrastructure Inspections

A Real- Time Multi-Camera Auto-Adjustment Framework for Infr...

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IEEE/SICE International Symposium on System Integration

作者： Chuong Phuoc Le Charles Ellison Steven Bunkley Hung La Anton Netchaev Department of Computer Science and Engineering Advanced Robotics and Automation (ARA) Lab University of Nevada Reno NV USA USACE Engineer Research and Development Center (ERDC) Information Technology Lab Vicksburg MS USA

In this paper, we proposed a novel multi-camera auto-adjustment framework for infrastructure inspections, specifically 3D point cloud mapping via lidar-camera fusion. Our method uses a single controller for consensus target brightness and adaptive lighting. In addition, a vignette correction filter was created to apply to images outputted from cameras to avoid dark strips on the point cloud data. This approach is designed to be a versatile, real-time friendly, and platform agnostic software stack.

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Experimental Study on the Improvement of Yaw Stability by Coordination Control between the Caudal Fin and Anal Fin

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Journal of Bionic Engineering 2022年第5期19卷 1261-1271页

作者： Jiang Ding Changzhen Zheng Chaocheng Song Qiyang Zuo Yaohui Xu Bingbing Dong Jiaxu Cui Kai He Fengran Xie College of Mechanical Engineering Guangxi UniversityNanning 530004China Guangxi Key Lab of Manufacturing System and Advanced Manufacturing Technology Nanning 530004China Shenzhen Institute of Advanced Technology Chinese Academy of SciencesShenzhen 518055China Shenzhen Key Laboratory of Precision Engineering Shenzhen 518055China University of Chinese Academy of Sciences Beijing 100049China College of Mechanical Automation Wuhan University of Science and TechnologyWuhan 430000China SIAT Branch Shenzhen Institute of Artificial Intelligence and Robotics for SocietyShenzhen 518055China

Due to the unique locomotion,the head-shaking problem of biomimetic robotic fish inevitably occurs during rectilinear locomotion,which strongly hinders its practical *** this paper,we experimentally study this problem by proposing the method of coordination control between the caudal fin and anal ***,an untethered biomimetic robotic fish,equipped with an anal fin,a caudal fin and two pectoral fins,is developed as the experimental ***,a Central Pattern Generator(CPG)-based controller is used to coordinate the motions of the anal fin and caudal ***,extensive experiments are conducted to explore different combinations of the flapping frequencies,the flapping amplitudes,and the phase differences between the anal fin and caudal ***,through proper control of the anal fin,the amplitude of the yaw motion can be as small as 4.32°,which sees a 65%improvement compared to the scenario without anal fin,and a 57%improvement compared to that with a stationary anal *** paper provides a novel way to alleviate the head-shaking problem for biomimetic robotic fish,and first test this method on an untethered,freely swimming robotic platform,which can shed light on the development of underwater robotics.

关键词： Biomimetic robotic fish Anal fin Head-shaking Yaw stability

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BRNES: Enabling Security and Privacy-Aware Experience Sharing in Multiagent Robotic and Autonomous Systems

BRNES: Enabling Security and Privacy-Aware Experience Sharin...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Md Tamjid Hossain Hung Manh La Shahriar Badsha Anton Netchaev The Advanced Robotics and Automation Lab Computer Science and Engineering University of Nevada Reno Nevada USA Bosch Engineering North America The U.S. Army Corps.

Although experience sharing (ES) accelerates multiagent reinforcement learning (MARL) in an advisor-advisee framework, attempts to apply ES to decentralized multiagent systems have so far relied on trusted environments and over-looked the possibility of adversarial manipulation and inference. Nevertheless, in a real-world setting, some Byzantine attackers, disguised as advisors, may provide false advice to the advisee and catastrophically degrade the overall learning performance. Also, an inference attacker, disguised as an advisee, may conduct several queries to infer the advisors' private information and make the entire ES process questionable in terms of privacy leakage. To address and tackle these issues, we propose a novel MARL framework (BRNES) that heuristically selects a dynamic neighbor zone for each advisee at each learning step and adopts a weighted experience aggregation technique to reduce Byzantine attack impact. Furthermore, to keep the agent's private information safe from adversarial inference attacks, we leverage the local differential privacy (LDP)-induced noise during the ES process. Our experiments show that our framework outperforms the state-of-the-art in terms of the steps to goal, obtained reward, and time to goal metrics. Particularly, our evaluation shows that the proposed framework is 8.32x faster than the current non-private frameworks and 1.41x faster than the private frameworks in an adversarial setting.

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