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检索条件"任意字段=Proceedings of the 3rd International Conference on Mechatronics and Robotics Engineering"

共 6132 条记录，以下是91-100 订阅

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HandEEGnet: A Kolmogorov-Arnold Network for Hand Movements Classification from Motor Imagery EEG 3

HandEEGnet: A Kolmogorov-Arnold Network for Hand Movements C...

引用

3rd IEEE international conference on robotics, Automation, Artificial-Intelligence and Internet-of-Things, RAAICON 2024

作者： Hasan, Tasnimul Hossain, A.B.M. Aowlad Biswas, Shuvagata Tazrin, Farhana Khulna University of Engineering & Technology Department of Biomedical Engineering Khulna9203 Bangladesh Khulna University of Engineering & Technology Department of Electronics and Communication Engineering Khulna9203 Bangladesh Khulna University of Engineering & Technology Department of Computer Science and Engineering Khulna9203 Bangladesh

ISBN: (纸本)9798331534400

Motor imagery-based BCI plays a vital role in controlling hand movements by processing and recognizing features from EEG signals associated with the imagination of those movements. In this paper, we present a Kolmogorov-Arnold Networks (KAN) based framework in order to classify the left and right-hand movements along with the absence of movement's intention from the electroencephalogram (EEG) signal. The emergence of KAN is expected to be a breakthrough concept in the artificial intelligence paradigm considering its learnable activation functions mechanism and interpretability opportunities. Preprocessing of the collected raw EEG data has been accomplished with band-pass filtering of EEG components of five well-matched channels and corresponding power spectral density feature extraction. We have used 15282 samples with annotated classes from a publicly available dataset to train, validate, and test the classifier. A comparative analysis of the performance of KAN and conventional Multi-Layer Perceptron (MLP) networks has been conducted in order to investigate the effectiveness of the KAN for this classification task. The proposed framework attains 96.14% classification accuracy for 3057 blind test samples, which is found to be better than the conventional MLP neural network approach (76.64% accuracy) and compatible with the existing techniques. The finding of this research might be useful in hand movement-related applications for robotics, prosthetics, and neuro-rehabilitation supports. © 2024 IEEE.

关键词： Multilayer neural networks

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Intelligent Fire Surveillance: A Deep Learning Framework for Accurate Indoor Fire Detection 3

Intelligent Fire Surveillance: A Deep Learning Framework for...

引用

3rd IEEE international conference on robotics, Automation, Artificial-Intelligence and Internet-of-Things, RAAICON 2024

作者： Maruf, Md. Paul, Bishow Jit Talukder, Labanya Islam, Mahmuda Rajshahi University of Engineering and Technology Rajshahi6204 Bangladesh

ISBN: (纸本)9798331534400

Fire is a naturally occurring but destructive phenomenon capable of causing extensive property damage and loss of life. Early detection is crucial for mitigating fire hazards, as it helps prevent the spread of fire, saves lives, and min-imizes infrastructure damage. Traditional fire detection often face challenges including low sensitivity, difficulties in large-scale deployment, high false alarm rates, and detection delays. This research presents an innovative fire detection system that integrates a Deep Learning model framework to monitor, detect, and warn about fires in indoor environments like buildings, rooms, and *** framework utilizes a pre-existing Convolutional Neural Network (CNN), specifically leveraging the VGG16 model, as the basis for its Deep Learning architecture. Through transfer learning, we develop a FireNET architecture specifically designed for fire detection tasks with an accuracy of 99.50%. This integration of Deep Learning in fire detection provides real-time detection with high speed and accuracy and effectively overcoming the limitations of traditional fire detection sensors. © 2024 IEEE.

关键词： Convolutional neural networks

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Trajectory optimization for spray-painting robot in Cartesian space based on consistency index of paint film thickness 3

Trajectory optimization for spray-painting robot in Cartesia...

引用

3rd international conference on Innovations and Development of Information Technologies and robotics, IDITR 2024

作者： Xu, Feng Zi, Bin Zhang, Dan School of Mechanical Engineering Hefei University of Technology Hefei China The Hong Kong Polytechnic University Department of Mechanical Engineering Hong Kong

ISBN: (纸本)9798350385694

In response to the issue of uneven paint film thickness in Z-shaped spray trajectories during camouflage coating operations, this paper presents a robot spray trajectory optimization method based on a consistency evaluation index of the paint film thickness. Firstly, for the Z-shaped spray trajectory of the robot spray gun, a linear trajectory with seventh-degree polynomial blends is used to generate multi-point spray trajectories within the camouflage color blocks. Then, based on the paint deposition model of the rectangular gun, a consistency evaluation index for the paint film thickness is established. Finally, with the minimization of the variance in paint thickness as the optimization objective, the optimal spray trajectory is generated based on a genetic algorithm, with the interpolation time interval as the decision variable. Simulation and experiment results validate the effectiveness of the proposed method, demonstrating its capability to achieve a relatively uniform paint thickness while realizing a Z-shaped spray trajectory planning for camouflage blocks in Cartesian space. © 2024 IEEE.

关键词： Genetic algorithms

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Bipartite Consensus of Multirobot Systems with an Event-Triggered Impulsive Strategy 3

Bipartite Consensus of Multirobot Systems with an Event-Trig...

引用

3rd international conference on Service robotics, ICoSR 2024

作者： Li, Hongtao Wang, Binrui Liu, Dan Fu, Lingkun College of Mechanical and Electrical Engineering China Jiliang University Hangzhou China College of Mechanical and Electrical Engineering China Jiliang University Key Laboratory of Online Detection Hangzhou China Science and Technology Innovation Research Institute Windey Energy Technology Group Co. Ltd. Hangzhou China

ISBN: (纸本)9798350367119

Motivated by the promising applications of multirobot systems (MRSs), this paper studies the bipartite consensus of MRSs with an event-triggered impulsive scheme. Because the system states are unavailable in many actual applications, we design the appropriate impulsive observers to estimate them. Moreover, to avoid the unnecessary waste of communication resources under general impulsive communication, the continuous event-triggered schemes are proposed to select appropriate impulsive time. Furthermore, several adaptive controllers are constructed to achieve bipartite consensus of MRSs. Finally, the scheme is verified to be effective by a simulation example. © 2024 IEEE.

关键词： Microrobots

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Path Planning of Mobile Robot Based on the Improved RRT-Connect Algorithm 3

Path Planning of Mobile Robot Based on the Improved RRT-Conn...

引用

3rd international conference on Service robotics, ICoSR 2024

作者： Wang, Jiqiang Zheng, Enhui College of Mechanical and Electrical Engineering China Jiliang University Hangzhou China

ISBN: (纸本)9798350367119

To address the issues of traditional RRT-Connect algorithms in global path planning, such as low exploration efficiency, slow convergence speed, and excessive path waypoints. In this paper, an improved RRT-Connect path planning algorithm is proposed. To enhance exploration efficiency, the algorithm constructs a generalized Voronoi diagram (GVD) to analyze obstacle distribution in the environment, which in turn generates multiple intermediate guide nodes to improve exploration efficiency. In addition, the algorithm combines the goal bias strategy and the concept of attractive field to assist the generation of new nodes to improve the path convergence speed. To ensure smoothness of the path, a two-way pruning strategy is used to eliminate redundant nodes on the initial path. Ultimately, the paths are trajectory optimized using the cubic spline interpolation algorithm so that they satisfy the kinematic constraints of the robot. The algorithm proposed in this paper will be compared with the traditional RRT-Connect algorithm with, RRT algorithm, and RRT∗ algorithm in two different environments. The results show a significant improvement over the traditional RRT-Connect algorithm. © 2024 IEEE.

关键词： Mobile robots

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Q-Learning for Stackelberg Games of Uncertain Nonlinear Systems 3

Q-Learning for Stackelberg Games of Uncertain Nonlinear Syst...

引用

3rd international conference on Service robotics, ICoSR 2024

作者： Tang, Wenbei Cui, Xiaohong Sun, Jun Deng, Jiaxian The College of Mechanical and Electrical Engineering China Jiliang University Hangzhou China China Jiliang University Zhejiang Province Key Laboratory of On-line Testing Equipment Calibration Technology Research Hangzhou China

ISBN: (纸本)9798350367119

The Stackelberg equilibrium approach is based on the traditional dynamic programming technique, which requires an understanding of the system model to solve the optimal control problem. Therefore, we propose a Q-learning algorithm based on actor-critic structure to solve the optimization problem of Stackelberg game in nonlinear systems with unknown system model data. Currently, the Q-learning algorithm is mainly used in the study of linear systems in this direction, and the study of nonlinear system problems is limited. In addition, the stability of the system is ensured by proving the consistency of the system state and the ultimate boundedness of the neural network weight estimation error. Finally, the effectiveness of the algorithm is verified by simulation experiment. © 2024 IEEE.

关键词： Dynamic programming

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The Rise of Intelligence: A Comprehensive Review on AI and AI Automation 3

The Rise of Intelligence: A Comprehensive Review on AI and A...

引用

3rd international conference on Communication, Control, and Intelligent Systems, CCIS 2024

作者： Bhardwaj, Cheshtaa Gla University Department of Computer Engineering and Applications Mathura India

ISBN: (纸本)9798331528201

This paper presents a comprehensive review of Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) technologies, focusing on their impact in driving AI automation across diverse sectors with a special emphasis on robotics. As AI continues to evolve, its integration into automation systems has revolutionized industries, enhancing efficiency, precision, and decision-making. The role of AI automation in robotics is critically examined, covering key architectural frameworks that enable autonomous operation and intelligent decision-making. Furthermore, the security aspects associated with AI in robotics, identifying attack surfaces and potential vulnerabilities has been analysed. This review highlights the transformative potential of AI automation while addressing the challenges and security concerns that accompany its deployment in modern systems, particularly in robotics. © 2024 IEEE.

关键词： Adversarial machine learning

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Design and Tracking Control of a Robot Arm for Climbing the Outer Wall of a Pipeline 3

Design and Tracking Control of a Robot Arm for Climbing the ...

引用

3rd international conference on Service robotics, ICoSR 2024

作者： Lei, Chunming Wang, Binrui Wang, Lina College of Mechanical and Electrical Engineering China Jiliang University Hangzhou China

ISBN: (纸本)9798350367119

Owing to the confined spatial constraints on the exterior of oil pipelines, the capability of a wall-climbing robot to inspect the welds is impeded by its lack of rotational mobility. To address this limitation, the present study initially develops a unidirectional articulated appendage integrated into the robot's design. The manipulator is mainly composed of steering engine, fixed synchronization belt and c ring rack. Secondly, the trajectory control of the needle manipulator in the working process has the disadvantages of large error deviation, poor robustness and low efficiency. A neural network adaptive control method is proposed. Confronted with trajectory deviations stemming from manipulator system inaccuracies and frictional disturbances, this study employs a Radial Basis Function (RBF) neural network for the identification and compensation of dynamic model uncertainties, thereby enhancing the precision of the actuating torque. Subsequently, by fine-tuning the adaptation law coefficients of the neural network weights, the formulated control strategy, inclusive of the identification outcomes, adheres to the Lyapunov stability criteria, thereby substantiating the system's dynamic stability. © 2024 IEEE.

关键词： Stability criteria

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Research on the surface topography inspection of sandpaper based on machine vision 3

Research on the surface topography inspection of sandpaper b...

引用

3rd international conference on Innovations and Development of Information Technologies and robotics, IDITR 2024

作者： Zheng, Huifeng Liu, Jinru Chen, Ge Xiao, Lei College of Mechanical Engineering Donghua University Shanghai China

ISBN: (纸本)9798350385694

To solve the problems of low efficiency and high subjectivity of existing sandpaper morphology parameter detection methods, machine vision methods are used to detect the surface morphology characteristics of sandpaper. A weighted decision matrix is established to select the important parameters that can reflect the topography of the sandpaper surface;Zeiss Smartproof5 fast turntable confocal microscope equipment is used to obtain the true-color view of different sandpaper samples, the pseudo-color view based on the height, and the XYZ three-dimensional point cloud of the sandpaper surface;the image is preprocessed by the methods of threshold segmentation and morphology processing, and then segmented by watershed segmentation;and the key topographic parameters of different sandpaper samples are calculated and compared. The key morphological parameters of different sandpaper samples were calculated and compared. The results show that the number of abrasive grains, abrasive grain size and other parameters increase with the increase of mesh size, while the uniformity of sandpaper distribution decreases with the increase of mesh size. The results of this study can provide a theoretical reference for the realization of automated inspection of sandpaper surface topography. © 2024 IEEE.

关键词： Computer vision

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Research on Infrared Detection and Identification of Internal Defects in Pipeline Wall-Climbing Robot 3

Research on Infrared Detection and Identification of Interna...

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3rd international conference on Service robotics, ICoSR 2024

作者： Liang, Xinlong Wang, Binrui Zhou, Kun Wu, Shanqiang Chen, Xianlei College of Mechanical and Electrical Engineering China Jiliang University Hangzhou China Zhoushan Institute of Calibration and Testing for Quality and Technology Supervision Zhoushan China

ISBN: (纸本)9798350367119

This paper presents the design of an infrared detection system integrated into a wall-climbing robot, enabling autonomous detection of internal defects within pipelines. The system is based on lock-in thermography technology, which involves generating periodic excitation to capture a sequence of thermal images using an infrared thermal imager. Subsequent processing includes S-G filtering and FFT transformation to analyze differences in surface thermal radiation amplitude and phase, thereby detecting internal defects in the test object. The experiment explores the detection effectiveness of defects of various sizes and depths under different lock-in frequencies. The results indicate that lock-in thermography detection technology exhibits favorable capabilities in detecting internal defects within a certain range. © 2024 IEEE.

关键词： Locks (fasteners)

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