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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Acuaviva, Antonio Bautista, Jesus Yao, Weijia Jimenez, Juan De Marina, Hector Garcia Universidad Complutense de Madrid Department of Computer Architecture and Automation Spain Department of Computer Engineering Automation and Robotics Granada Spain Hunan University School of Robotics China

ISBN: (纸本)9798350316339

We present a solution for locating the source, or maximum, of an unknown scalar field using a swarm of mobile robots. Unlike relying on the traditional gradient information, the swarm determines an ascending direction to approach the source with arbitrary precision. The ascending direction is calculated from field strength measurements at the robot locations and their relative positions concerning the swarm centroid. Rather than focusing on individual robots, we focus the analysis on the density of robots per unit area to guarantee a more resilient swarm, i.e., the functionality remains even if individuals go missing or are misplaced during the mission. We reinforce the algorithm's robustness by providing sufficient conditions for the swarm shape so that the ascending direction is almost parallel to the gradient. The swarm can respond to an unexpected environment by morphing its shape and exploiting the existence of multiple ascending directions. Finally, we validate our approach numerically with hundreds of robots. The fact that a large number of robots with a generic formation always calculate an ascending direction compensates for the potential loss of individuals. © 2024 IEEE.

关键词： Microrobots

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Contact Force Estimation by Fusing Current and Tactile Information Through KF for Robot Arm

Contact Force Estimation by Fusing Current and Tactile Infor...

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2024 IEEE International Conference on robotics and Biomimetics, ROBIO 2024

作者： Tian, Yujie Guang, Chengfang Luo, Ruiqing Bao, Sheng Yuan, Jianjun Du, Liang Hu, Zhengtao School of Mechatronic Engineering and Automation Shanghai University Shanghai Key Laboratory of Intelligent Manufacturing and Robotics Shanghai China Shanghai Robotics Institute School of Mechatronic Engineering and Automation Shanghai University Shanghai China

ISBN: (纸本)9781665481090

Accurate contact force estimation is crucial for interactions between the robot arm and its environment. Presently, contact force estimation based on current information often suffers from biases caused by unmodeled errors, noise, and various other factors. In contrast, tactile sensors information effectively complements current information, enhancing the estimation of contact forces in robot arm interactions. To improve the accuracy of force estimation without force/torque sensors, we propose an information fusion method utilizing Kalman Filter (KF) to incorporate motor current with the tactile sensor for a nursing robot arm with Differential Modular Joints (DMJ). The coupling dynamic model of the DMJ and the contact force estimation model of the tactile sensor are established respectively. Subsequently, a linear KF fusion method is introduced based on these two methods. The experimental results indicate that contact force can be reliably estimated without force/torque sensors, significantly enhancing the accuracy of force estimation. © 2024 IEEE.

关键词： Robotic arms

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A study on design and control of Omni-directional mecanum wheels based AGV system 14

A study on design and control of Omni-directional mecanum wh...

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14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023

作者： Bhargava, Ankur Singholi, Ajay S. Suhaib, Mohd. Jamia Millia Islamia Faculty of Engineering and Technology Delhi India University School of Robotics & Automation Robotics & Automation Delhi India

ISBN: (纸本)9798350335095

Automated guided vehicles (AGVs) have emerged as crucial equipment in sectors that demand reliable and effective transportation and material handling systems. The design and control features of AGV systems are discussed in general terms in this study, with an emphasis on important factors and recent developments. The vehicle platform, sensing and perception systems, navigational algorithms, and control architecture are all essential parts of the design of an AGV system. To fit the application's unique requirements, the vehicle platform must be properly developed, taking into account elements like load capacity, maneuverability, and power supply. The AGV can sense its surroundings and maneuver on its own thanks to the choice and integration of sensors including LiDAR, cameras, and encoders. Simultaneous Localization and Mapping (SLAM), one of the most sophisticated perception algorithms, is essential for precisely mapping the environment and locating the AGV within it. Because of navigation algorithms, AGVs can efficiently plan their routes, avoid dangers, and reach their targets. Methods for establishing a path enable smooth, collision-free travel by accounting for factors including distance, time, and dynamic restrictions. Real-time control systems regulate the AGV's speed, acceleration, and steering, enabling accurate and secure operation in a variety of situations. The controls design should enable monitoring of the system and detection of problems in along with enabling integration of perception, navigating, and control modules. This paper examines the mechanical and electrical design of a test prototype autonomous guided vehicle (AGV). The SLAM technique apply in the present work successfully resolves the localization problem in conjunction with the navigation algorithm. © 2023 IEEE.

关键词： Electric loads

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Advancement in CFD and Responsive AI to Examine Cardiovascular Pulsatile Flow in Arteries:A Review

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Computer Modeling in engineering & Sciences 2024年第12期141卷 2021-2064页

作者： Priyambada Praharaj Chandrakant R.Sonawane Arunkumar Bongale Department of Engineering Science and Humanities JSPM Rajarshi Shahu College of EngineeringPune411033India Robotics and Automation Department Symbiosis Institute of TechnologySymbiosis Institute(Deemed)UniversityPune412115India

This paper represents a detailed and systematic review of one of the most ongoing applications of computational fluid dynamics(CFD)in biomedical *** its various engineering applications,CFD has started to establish a presence in the biomedical *** abnormality,a familiar health issue,is an essential point of investigation by research *** modalities provide cardiovascular structural information but give insufficient information about the hemodynamics of *** study of hemodynamic parameters can be a potential measure for determining cardiovascular *** studies have explored the rheological behavior of blood experimentally and *** paper provides insight into how researchers have incorporated the pulsatile nature of the blood experimentally,numerically,or through various simulations over the *** focuses on how machine learning platforms derive outputs based on mass and momentum conservation to predict the velocity and pressure profile,analyzing various cardiac diseases for clinical *** will pave the way toward responsive AI in cardiac healthcare,improving productivity and quality in the healthcare *** paper shows how CFD is a vital tool for efficiently studying the flow in *** review indicates this biomedical simulation and its applications in healthcare using machine learning and *** AI-based CFD models can impact society and foster the advancement towards responsive AI.

关键词： Pulsatile flow cardiovascular CFD simulation patient-specific GPU-accelerated responsive AI

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High-Velocity Projectile Impact Behaviour of Friction Stir Welded AA7075 Thick Plates

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Defence Technology（防务技术） 2023年第11期29卷 153-163页

作者： R.Praveen S.R.Koteswara Rao G.Selvakumar R.Damodaram Department of Robotics and Automation Karpaga Vinayaga College of Engineering and TechnologyChengalpattu603308TamilNaduIndia Department of Mechanical Engineering Sri Sivasubramaniya Nadar College of EngineeringChennai603110TamilNaduIndia

In this study, high velocity impact behaviour of friction stir welded AA7075-T651 25 mm thick plates were investigated using a 7.62 mm × 51 mm lead core and 7.62 mm × 39 mm steel core projectiles. Prior to ballistic trails, mechanical and metallurgical properties of friction stir welded AA 7075-T651 25 mm thick plates were studied. Microstructural and hardness studies revealed that friction stir welds constituted three distinct regions namely Weld Nugget(WN), Thermo-Mechanically Affected Zone(TMAZ) and Heat Affected Zone(HAZ). Base Material(BM) and all three weld regions were ballistically tested as per military standard NIJ.0108.01 using lead and steel core bullets at maximum permissible velocities of 830 ± 20 and 700 ± 30 m/s, respectively. It has been found that base material(AA7075-T651)and all three weld regions of 25 mm thick plates were able to resist perforation by both types of projectiles used. However depth of penetration has been found to increase from BM to WN, HAZ and TMAZ for both types of projectiles. In all cases steel core projectiles caused higher depth of penetration compared to those caused by lead core projectiles. TMAZs of the friction stir welds were found to be the weakest zone. The fracture that occurred in the base material was spall fragmentation indicating brittle failure, whereas all zones of friction stir welded AA7075-T651 targets with a front petalling, indicating ductile failure. The post-ballistic tested samples showed no significant change in the microstructure of the BM and WN. On the other hand, TMAZ and HAZ showed severe grain deformation in the direction of projectile penetration, and the formation of adiabatic shear bands(ASB). This work showed that 25 mm thick friction stir welded AA7075-T651 joints responded well to ballistic impact loads, making them a good choice for light combat vehicles.

关键词： Aluminum alloy Thick plate Friction stir welding Ballistic performance Depth of penetration

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Autonomous IoT-Integrated Tomato Plant Disease Detection: Harnessing YOLOv8 Algorithm and Micro-Navigation for Precision Agriculture 6

Autonomous IoT-Integrated Tomato Plant Disease Detection: Ha...

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6th IEEE International Conference on Recent Advances in Intelligent Computational Systems, RAICS 2024

作者： Dinesh, Randhir Mohan, Hemanth Kumar, Abhiraj S Mathai, Anwin Deepak, S. Robotics And Automation Kerala India Gec Thrissur Dept of Electronics Engineering Kerala India

ISBN: (纸本)9798350381689

The nation of India, with abundant biodiversity, must contend with the effects of climate change on ecosystems and habitats. The tomato, or Solanum lycopersicum, is a critically important fruit utilized extensively in Indian and Western cuisines. However, the tomato is a fruit that may contract illness because of pest infestations, bacterial activity, microbes, and changes in the climate. Given the necessity for mass production, which renders 'hand-picking' unfeasible, automation of a tomato field would be crucial. This would necessitate innovative solutions for disease diagnosis and classification in a large-scale production. This study examines various approaches related to tomato iden-tification, emphasizing performance analysis. To detect pests and illnesses in crops, the suggested method includes an autonomous mobile robot fitted with sensors, such as RGB cameras and Ultrasonic Sensors enhanced with Wi-Fi-enabled data transfer for IoT technology. The RGB camera takes crop visuals in real time and uses image processing, deep learning techniques, and the YOLOv8 algorithm to identify disease symptoms. To make the suggested mobile robot, an effective and long-lasting instrument for disease management in agriculture Micro-ROS is used. Its ability to identify illnesses quickly reduces the environmental impact and guarantees food safety, which is a big step toward a sustainable agricultural future. © 2024 IEEE.

关键词： Fruits

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Design and Development of a Visual - SLAM based Automated Guided Vehicle 5

Design and Development of a Visual - SLAM based Automated Gu...

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5th IEEE International Conference on Advances in Electronics, Computers and Communications, ICAECC 2023

作者： Bhargava, Ankur Singholi, Ajay S. Suhaib, Mohd. Faculty of Engineering and Technology Jamia Millia Islamia Delhi India University School of Robotics & Automation India Robotics & Automation Delhi India

ISBN: (纸本)9798350305449

The automobile industry is currently undergoing fast change as big manufacturers devote their attention to the development of future self- driving vehicles or automated guided vehicles. As a result, mobile robots and current automotive technologies are integrating to create the area of autonomous navigation. The camera sensor is the one garnering the most attention in terms of autonomy sensor research due to the large amount of information it provides for object detection and classification algorithms in addition to depth, coloring, size, and texture recognition. In the last ten years, there have been significant advancements in computing capabilities and image analysis algorithms. The requirement for developing low-level motion controllers grew as a consequence of the increase in machine vision performance and capabilities. This article discusses mecanum wheel mobile robotic applications of vision and SLAM-based motion controller. When using sensors like cameras or Lidar, autonomous mobile robots usually use the vision- based & simultaneous localization and mapping (SLAM) technology. The four-wheeled autonomous robot model that was utilized in the studywas created using a Jetson board with high performance processor, a depth camera, and LIDAR sensors along with ROS's RVIZ software. © 2023 IEEE.

关键词： Mobile robots

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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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Enhanced YOLOv8- Driven Traffic Rule Violation Detection with ROS-Integrated Autonomous Drone Navigation 6

Enhanced YOLOv8- Driven Traffic Rule Violation Detection wit...

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6th IEEE International Conference on Recent Advances in Intelligent Computational Systems, RAICS 2024

作者： Mohan, Hemanth Dinesh, Randhir S Kumar, Abhiraj Mathai, Anwin Deepak, S. Robotics And Automation Kerala India Gec Thrissur Dept of Electronics Engineering Kerala India

ISBN: (纸本)9798350381689

Employing autonomous drones, an expanded per-spective of the traffic situation may be obtained, covering more terrain than the existing monitoring system that depends on stationary cameras. Drones may also navigate through challenging-to-reach locations and complicated terrain, giving a more ac-curate and comprehensive view of the violations of traffic laws that are taking place nearby. Drones equipped with path planning implemented using ROS and the ability to detect traffic violations can greatly surpass the existing surveillance system. Proposed drones can record live videos of traffic violations, which deep learning algorithms can process to pinpoint the exact offense. These drones can quickly and accurately identify a variety of traffic infractions, such as speeding, illegal parking, and careless driving, by utilizing deep learning algorithms which utilize the YOLOv8 algorithm. © 2024 IEEE.

关键词： Deep learning

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