Improved Multi-Stream Convolutional Block Attention Module for sEMG-Based Gesture Recognition

Frontiers in Bioengineering and Biotechnology, Journal Year: 2022, Volume and Issue: 10

Published: June 7, 2022

As a key technology for the non-invasive human-machine interface that has received much attention in industry and academia, surface EMG (sEMG) signals display great potential advantages field of collaboration. Currently, gesture recognition based on sEMG suffers from inadequate feature extraction, difficulty distinguishing similar gestures, low accuracy multi-gesture recognition. To solve these problems new network called Multi-stream Convolutional Block Attention Module-Gate Recurrent Unit (MCBAM-GRU) is proposed, which signals. The multi-stream formed by embedding GRU module CBAM. Fusing ACC further improves action experimental results show proposed method obtains excellent performance dataset collected this paper with accuracies 94.1%, achieving advanced 89.7% Ninapro DB1 dataset. system high classifying 52 kinds different delay less than 300 ms, showing terms real-time human-computer interaction flexibility manipulator control.

Language: Английский

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Photoelastic Stress Field Recovery Using Deep Convolutional Neural Network

Frontiers in Bioengineering and Biotechnology, Journal Year: 2022, Volume and Issue: 10

Published: March 21, 2022

Recent work has shown that deep convolutional neural network is capable of solving inverse problems in computational imaging, and recovering the stress field loaded object from photoelastic fringe pattern can also be regarded as an problem process. However, formation affected by geometry specimen experimental configuration. When produces complex distribution, traditional analysis methods still face difficulty unwrapping. In this study, a based on encoder-decoder structure proposed, which accurately decode distribution information images generated under different configurations. The proposed method validated synthetic dataset, quality model evaluated using mean squared error (MSE), structural similarity index measure (SSIM), peak signal-to-noise ratio (PSNR), other evaluation indexes. results show recovery achieve average performance more than 0.99 SSIM.

Language: Английский

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Performance evaluation of PSO-PID and PSO-FLC for continuum robot’s developed modeling and control

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Jan. 6, 2024

Continuum robots are complex structures that require sophisticated modeling and control methods to achieve accurate position motion tracking along desired trajectories. They highly coupled, nonlinear systems with multiple degrees of freedom pose a significant challenge for conventional approaches. In this paper, we propose system dynamic model based on the Euler-Lagrange formulation assumption piecewise constant curvature (PCC), where accounts elasticity gravity effects continuum robot. We also develop apply particle swarm optimization (PSO) algorithm optimize parameters our developed controllers: an inverse proportional integral derivative (PID) controller fuzzy logic (FLC), use time absolute error (ITAE) as objective function PSO algorithm. validate proposed optimized controllers through different designed trajectories, simulated using unique animated MATLAB simulation. The results show PSO-PID improves rise time, overshoot percentage, settling by 16.3%, 31.1%, 64.9%, respectively, compared PID without PSO. PSO-FLC shows best performance among all controllers, 0.7 s 0.4 s, leading highest level precision in trajectory tracking. ITAE is 11.4% 29.9% lower than FLC respectively.

Language: Английский

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Biomimetic Vision for Zoom Object Detection Based on Improved Vertical Grid Number YOLO Algorithm

Frontiers in Bioengineering and Biotechnology, Journal Year: 2022, Volume and Issue: 10

Published: May 20, 2022

With the development of bionic computer vision for images processing, researchers have easily obtained high-resolution zoom sensing images. The drones equipped with high-definition cameras has greatly increased sample size and image segmentation target detection are important links during process information. As biomimetic remote usually prone to blur distortion in imaging, transmission processing stages, this paper improves vertical grid number YOLO algorithm. Firstly, light shade a were abstracted, grey-level cooccurrence matrix extracted feature parameters quantitatively describe texture characteristics image. Simple Linear Iterative Clustering (SLIC) superpixel method was used achieve light/dark scenes, saliency area obtained. Secondly, model segmenting dark scenes established made dataset meet recognition standard. Due refraction passing through lens other factors, difference contour boundary value between pixel background would make it difficult detect target, pixels main part separated be sharper edge detection. Thirdly, algorithm an improved proposed real time on processed array. adjusted aspect ratio modified grids network structure by using 20 convolutional layers five maximum aggregation layers, which more accurately adapted "short coarse" identified object information density. Finally, comparison mainstream algorithms different environments, test results aid showed that high spatial resolution images, higher accuracy than had real-time performance accuracy.

Language: Английский

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Construction Project Cost Prediction Method Based on Improved BiLSTM

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(3), P. 978 - 978

Published: Jan. 23, 2024

In construction project management, accurate cost forecasting is critical for ensuring informed decision making. this article, a prediction method based on an improved bidirectional long- and short-term memory (BiLSTM) network proposed to address the high interactivity among data difficulty in feature extraction. Firstly, correlation between cost-influencing factors unilateral calculated via grey analysis select characteristic index. Secondly, BiLSTM used capture temporal interactions at deep level, hybrid attention mechanism incorporated enhance model’s extraction capability comprehensively features data. Finally, hyperparameter optimisation particle swarm algorithm using accuracy as fitness function of algorithm. The MAE, RMSE, MPE, MAPE, coefficient determination simulated results dataset are 7.487, 8.936, 0.236, 0.393, 0.996%, respectively, where MPE positive coefficient. This avoids serious consequences underestimating cost. Compared with unimproved BiLSTM, MAPE reduced by 15.271, 18.193, 0.784%, which reflects superiority effectiveness can provide technical support estimation field.

Language: Английский

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Multi-Objective Location and Mapping Based on Deep Learning and Visual Slam

Sensors, Journal Year: 2022, Volume and Issue: 22(19), P. 7576 - 7576

Published: Oct. 6, 2022

Simultaneous localization and mapping (SLAM) technology can be used to locate build maps in unknown environments, but the constructed often suffer from poor readability interactivity, primary secondary information map cannot accurately grasped. For intelligent robots interact meaningful ways with their environment, they must understand both geometric semantic properties of scene surrounding them. Our proposed method not only reduce absolute positional errors (APE) improve positioning performance system also construct object-oriented dense point cloud output model each object reconstruct indoor scene. In fact, eight categories objects are for detection using coco weights our experiments, most actual reconstructed theory. Experiments show that number points is significantly reduced. The average error Technical University Munich (TUM) datasets very small. camera reduced introduction constraints, improved. At same time, algorithm segment environment high accuracy.

Language: Английский

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Kinematics characteristics analysis of a 3-UPS/S parallel airborne stabilized platform

Aerospace Science and Technology, Journal Year: 2023, Volume and Issue: 134, P. 108163 - 108163

Published: Feb. 3, 2023

Language: Английский

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Target Detection Based on Two-Stream Convolution Neural Network With Self-Powered Sensors Information

IEEE Sensors Journal, Journal Year: 2022, Volume and Issue: 23(18), P. 20681 - 20690

Published: Nov. 16, 2022

With the rapid development of artificial intelligence, a neural network is widely used in various fields. The target detection algorithm mainly based on network, but accuracy greatly related to complexity scene and texture. A RGB-D image from perspective lightweight model integration depth map overcome weak environmental illumination with self-powered sensors information proposed. This article analyzes structure YOLOv4 MobileNet, compares variation parameter numbers between depthwise separable convolution convolutional networks, combines advantages MobileNetv3 network. main three effective feature layers replaced by for initial layer extraction strengthen At same time, standard models are convolution. proposed method compared YOLOv4-MobileNetv3 this article, experimental results show that retains its original accuracy, size about 23% model, processing speed 42% higher than can still reach 83% environment poor lighting conditions.

Language: Английский

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Real-time visual SLAM based YOLO-Fastest for dynamic scenes

Measurement Science and Technology, Journal Year: 2024, Volume and Issue: 35(5), P. 056305 - 056305

Published: Feb. 5, 2024

Abstract Within the realm of autonomous robotic navigation, simultaneous localization and mapping (SLAM) serves as a critical perception technology, drawing heightened attention in contemporary research. The traditional SLAM systems perform well static environments, but real physical world, dynamic objects can destroy geometric constraints system, further limiting its practical application world. In this paper, robust RGB-D system is proposed to expand number points scene by combining with YOLO-Fastest ensure effectiveness model construction, then based on that, new thresholding designed differentiate features objection bounding box, which takes advantage double polyline residuals after reprojection filter feature points. addition, two Gaussian models are constructed segment moving box depth image achieve effect similar instance segmentation under premise ensuring computational speed. experiments conducted sequences provided TUM dataset evaluate performance method, results show that root mean squared error metric absolute trajectory algorithm paper has at least 80% improvement compared ORB-SLAM2. Higher robustness environments both high low DS-SLAM Dynaslam, effectively provide intelligent navigation for mobile robots.

Language: Английский

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Inverse kinematics solution method based on workspace analysis and iterative step coefficient adjustment of general robot

Measurement, Journal Year: 2025, Volume and Issue: unknown, P. 116807 - 116807

Published: Jan. 1, 2025

Language: Английский

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