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检索条件"机构=Mechatronics and Robotics Engineering"

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Explainable Deep Learning for Brain-Computer Interfaces through Layerwise Relevance Propagation

Explainable Deep Learning for Brain-Computer Interfaces thro...

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International Winter Workshop on Brain-Computer Interface (BCI)

作者： Vladislav Mun Berdakh Abibullaev Computer Science Department School of Engineering and Digital Sciences Nazarbayev University Kazakhstan Robotics and Mechatronics Department School of Engineering and Digital Sciences Nazarbayev University Kazakhstan

With an ever-growing demand for BCI-based systems, numerous algorithms and machine learning systems have been proposed over the past few decades. Although state-of-theart approaches have reached practically appropriate levels of accuracy, most are often regarded as black-box models, which need more explainability. However, for cases where a Neural Network is used as the base for a classifier, a Layerwise Relevance Propagation (LRP) approach can be utilized to analyze the decision boundaries considered by the network. By calculating the importance of the neuron in each layer, the LRP can also be used as an effective model complexity reduction technique through the inactivation (pruning) of the neural pathways. The following work investigates the usability of the LRP framework in the field of BCI. This study provides an example of the practical application of the LRP with respect to the EEG (ERP) dataset, along with visual heatmap and scalp map examples of the LRP. Furthermore, the work analyzes the impact of network pruning on heatmap visualization and the model’s accuracy while also practically determining the maximum cutoff range for pruning BCI models.

关键词： Heating systems Deep learning Analytical models Visualization Brain modeling Transformers Electroencephalography

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Enhancing UAV Autonomous Navigation in Indoor Environments Using Reinforcement Learning and Convolutional Neural Networks 22

Enhancing UAV Autonomous Navigation in Indoor Environments U...

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22nd IEEE International Symposium on Intelligent Systems and Informatics, SISY 2024

作者： Safarpour Motealegh Mahalegi, Homayoun Farhadi, Amirfarhad Molnar, Gyorgy Nagy, Eniko Obuda University Institute of Mechatronics and Vehicle Engineering Budapest Hungary Islamic Azad University Department of Computer Engineering Science and Research Branch Tehran Iran Obuda University Hungary Szechenyi University Apaczai Csere János Faculty of Humanities Education and Social Sciences Kando Kalman Faculty of Electrical Engineering Budapest Gyor Hungary Obuda University Antal Bejczy Center for Intelligent Robotics John von Neumann Faculty of Informatics Budapest Hungary

ISBN: (纸本)9798350385601

In recent years, the number of unmanned aerial vehicle (UAV) applications has increased. However, navigating them indoors is still tricky because no GPS signals are available, and the obstacles constantly change. This study exploits the collaboration between convolutional neural networks (CNNs) and reinforcement learning (RL) to overcome these challenges, improving the level of independence of UAVs in indoor settings. We present a new technique known as potential-based reward shaping, which directly incorporates expert knowledge into the reinforcement learning framework. This technique efficiently addresses the problem of sparse rewards that often hinder learning in conventional RL configurations. In addition, we have created a reflective reinforcement learning agent that systematically assesses its actions to prioritize those that result in the most substantial enhancements. We have extensively evaluated the performance of our method with the High-Definition Indoor Navigation (HDIN) dataset to show that our method continuously outperformed current non-introspective RL techniques in terms of decision-making speed and navigation accuracy in this evaluation. The results show that this new CNN-RL combination is feasible and suggests a scalable method for complex indoor navigation problems. © 2024 IEEE.

关键词： Convolutional neural networks

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Robotic Device for Active-Passive Mechanotherapy of the Ankle Joint

Robotic Device for Active-Passive Mechanotherapy of the Ankl...

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International Conference on Industrial engineering, Applications and Manufacturing (ICIEAM)

作者： Jamil Safarov Egor Tistsov Sergey Jatsun Dept. of Chemical and Metallurgical engineering Azerbaijan Technical University Baki Azerbaijan Dept. of Mechanics Mechatronics and Robotics South-West State University Kursk Russia

ISBN: (数字)9798350395013

ISBN: (纸本)9798350395020

This paper describes the design and control system of a robotic device for active-passive mechanotherapy of the ankle joint. The paper raises the question of the importance of these developments in modern rehabilitation, provides examples of work in this area, and also indicates the difficulties in organizing a control system for such a device, due to the spasticity and musculoskeletal contracture of the ankle joint, as well as the general uncertainty and individuality of the muscular system of the ankle joint during rehabilitation. The paper describes the design of the device, the location of the measuring modules, and the operating principle of the adaptive control system for this device. Data obtained during experimental studies are also presented and the influence of various factors during rehabilitation procedures on the behavior of the musculoskeletal system is described. This paper describes the mathematical modeling of the behavior of this system, and indicators of the stiffness and viscosity of the musculoskeletal system are derived, allowing the adaptation of device control algorithms.

关键词： Viscosity Uncertainty Muscles Control systems Mathematical models Physiology Trajectory

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Innovative and Interdisciplinary Approach for Offering the Master of Science Degree in mechatronics

Innovative and Interdisciplinary Approach for Offering the M...

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2020 Conference for Industry and Education Collaboration, CIEC 2020

作者： Sergeyev, Aleksandr Minerick, Adrienne Irwin, John Mechatronics Electrical and Robotics Engineering Technology College of Computing/Manufacturing and Mechanical Engineering Technology Michigan Technological University HoughtonMI United States

mechatronics is the synergistic integration of electrical and mechanical engineering, robotics, computational hardware, and software in the design of products and processes. mechatronics is an essential foundation for the expected growth in automation and manufacturing. There is a demand for graduate education in mechatronics as the landscape of engineering programs has changed in the past decade, shifting from traditional degrees leading directly to closely aligned positions in industry, to preparing individuals with advanced technical competencies capable of engaging in interdisciplinary research and industry applications. The proposed MS degree in mechatronics at Michigan Tech has a very flexible structure consisting of five pathways allowing students from technology, traditional engineering, community colleges, other institutions, and industry representatives to pursue an advanced degree in this emerging field. Students enrolled in the program have three graduation options: coursework, research with thesis, and internship with industry and report options. The industry-driven curriculum developed for the proposed program addresses the need for a skilled advanced manufacturing workforce and accelerate the development of a digitally-savvy workforce for emerging manufacturing technologies. It focuses on core technical skills, advanced technical design skills, and core technical implementation/instrumentation skills that are used in the design and manufacturing of control systems and devices used in consumer products, aerospace and military applications, automotive and other advanced manufacturing industries. In this paper, authors provide details on organizational and administrative structure of the degree. Copyright ©2020, American Society for engineering Education

关键词： Students

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Swarm robotics for Autonomous Aerial Robots: Features, Algorithms, Control Techniques, and Challenges

Swarm Robotics for Autonomous Aerial Robots: Features, Algor...

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Emerging Smart Technologies and Applications (eSmarTA), International Conference on

作者： Yunes Alqudsi Murat Makaraci Aerospace Engineering Department Faculty of Aeronautics and Astronautics Kocaeli University Kocaeli Türkey Mechanical Engineering Department Faculty of Engineering Kocaeli University Kocaeli Türkey Mechatronics and Robotics Engineering Department Faculty of Engineering & IT Taiz University Taiz Yemen

ISBN: (数字)9798350354133

ISBN: (纸本)9798350354140

With the aim of revolutionizing various industries, the field of Swarm robotics (SRs) continuously offers efficient solutions to complex tasks. This paper provides a comprehensive review of recent advancements and emerging trends in SR, with a specific focus on the coordination and control of Swarm Aerial Robots (SARs). It examines the key features and characteristics of SR, its integration with swarm intelligence, and fundamental algorithms such as Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Differential Evolution (DE). The paper also discusses various swarm control techniques, infrastructure requirements, and challenges associated with implementing SR in Aerial Robots. Additionally, the paper outlines future research directions, emphasizing the need for robust, energy-efficient, adaptive algorithms and ethical considerations in deploying autonomous Aerial robot swarms. This study aims to provide a solid foundation for researchers and practitioners, paving the way for future advancements and interdisciplinary collaboration in this promising field.

关键词： Industries Ethics Reviews Swarm robotics Autonomous aerial vehicles Solids Market research

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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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Multi-layer Disturbance Observer-based Wheel Speed Control for Electric Vehicles

Multi-layer Disturbance Observer-based Wheel Speed Control f...

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Annual Conference of Industrial Electronics Society

作者： Yussuf Shakhin Ahmad Bala Alhassan Binh-Minh Nguyen Ton Duc Do Dept. of Robotics and Mechatronics School of Engineering and Digital Science (SEDS) Nazarbayev University Astana Kazakhstan Dept. of Advanced Energy The University of Tokyo Tokyo Japan

ISBN: (数字)9781665464543

ISBN: (纸本)9781665464550

As the adoption of electric vehicles (EVs) increases globally, there is a need to provide effective control for the safety and stability of the vehicles. In this paper, a cascade observer-based wheel speed control of an EV is proposed. The scheme uses three-loop cascade observers to estimate the wheel speed, which is often difficult to measure and critical for the EV’s control. The study only uses the measurement of the motor speed and torque to estimate the wheel speed from the observation of the total disturbances acting on the EV. A PID control is then designed for the control of the wheel speed using the estimated speed. The effectiveness of the designed observers and the wheel speed control is investigated using Matlab simulation under the influence of parametric uncertainties and external disturbance.

关键词： Torque Uncertainty Simulation Velocity control Wheels Motors Electric vehicles Stability analysis Safety Torque measurement

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Synchronization Control of Dual Motor Driving Steer by Wire System

Synchronization Control of Dual Motor Driving Steer by Wire ...

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IEEE Conference on Vehicle Power and Propulsion (VPPC)

作者： Insu Chung Sunyeop Lee Kanghyun Nam Younghoon Seo Sehoon Oh School of Mechanical Engineering Yeungnam University Gyeongsan Republic of Korea Department of Robotics and Mechatronics Engineering Daegu Gyeongbuk Institute of Science & Technology Daegu Republic of Korea

The Steer by Wire (SbW) system is a system that replaces the mechanical connection between the steering wheel and the vehicle's wheels with electrical signals to control steering. Dual motor driving SbW is designed with physical redundancy in case the SbW system does not operate normally. The system's mechanism requires synchronization control between the two motors to maintain driver safety in response to external disturbances and changes in driving conditions. This paper presents a position control scheme that utilizes the mean and difference of the two motor angles to directly control tracking performance and synchronization error. To apply the proposed method, the system's dynamics were theoretically analyzed, and a controller was designed based on that analysis. Finally, the proposed control scheme's performance is validated through experiments.

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Task-Oriented Stiffness Setting for a Variable Stiffness Hand

Task-Oriented Stiffness Setting for a Variable Stiffness Han...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Ana Elvira H. Martin Ashok M. Sundaram Werner Friedl Virginia Ruiz Garate Máximo A. Roa DLR the Institute of Robotics and Mechatronics German Aerospace Center Wessling Germany Mondragon Unibertsitatea Faculty of Engineering Bilbao Spain Bristol Robotics Laboratory University of the West of England Bristol United Kingdom

The integration of variable stiffness actuators (VSA) in robotic systems endows them with intrinsic flexibility and therefore robustness to unknown disturbances. However, this characteristic presents a challenge: choosing the best intrinsic stiffness setting guaranteeing the required force ap-plication capability while keeping the system as adaptable to uncertainties as possible. This paper proposes a method to set the optimal stiffness for a multi-finger VSA hand to perform a desired manipulation task. The task is generically represented as a force (with unknown magnitude) applied along a reference direction. According to the force application's direction and the hand's kinematic state, the fingers assume a certain role to split the collective force application. We employ the endpoint stiffness ellipsoid to analyze the required finger stiffness to fulfill the task. We evaluate the optimized stiffness settings in a door opening application with an iterative adaption of the stiffness behavior to handle the unknown force requirement. The results show a successful collective behavior of the fingers, where the stiffness setting considers a task-oriented force-adaptability trade-off and effective use of independent VSA fingers.

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Computational Intelligence Router of Machine and Artificial Intelligence Learning for the Expansion of Agriculture's Manufacturing Sector 3

Computational Intelligence Router of Machine and Artificial ...

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3rd International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2023

作者： Raman, Ramakrishnan Alanya-Beltran, Joel Akram, Shaik Vaseem Shah, Heli Sanjay, P.C. Ponnusamy, R. Symbiosis Institute of Business Management Pune Maharashtra Pune India Universidad Tecnológica Del Perú Peru Uttaranchal University Uttaranchal Institute of Technology India Parul University Mechatronics & Robotics Pit India India Chennai Institute of Technology Department of Computer Science & Engineering India

ISBN: (纸本)9798350399264

The economic sector includes agriculture as a major player. Around the world, the primary issue and hot topic is agriculture automation. As a result of the population boom, there is a huge increase in the need for both jobs and food. Farmers employed traditional techniques, which included insufficient to meet these needs. This led to the introduction of new automated techniques. These innovative techniques supplied the world's food needs while giving billions of people access to jobs. An agricultural revolution has been sparked by artificial intelligence. With the use of this technology, crop yields are now more resistant to many conditions like population increase, climate change, job troubles, and food security concerns. The primary goal of this study is to evaluate the numerous ways artificial intelligence is being used in agriculture, including the use of sensors and other tools built into drones and robots for weeding, spraying, and irrigation. The excessive use of pesticides, herbicides, water, and other resources is reduced by these technologies, and the soil fertility is maintained. They also aid in the effective use of labor, which raises productivity and quality. In order to provide a concise summary of the current state of agricultural automation, including the use of drones and robots for weeding, this study analyses the research of several researchers. Along with two automated weeding strategies, the various ways of soil water sensing are described. This study discusses the use of drones as well as the numerous spraying and crop monitoring techniques that may be utilized with them. © 2023 IEEE.

关键词： Drones

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