Genetic Algorithm-Based Trajectory Optimization for Digital Twin Robots

Frontiers in Bioengineering and Biotechnology, Год журнала: 2022, Номер 9

Опубликована: Янв. 10, 2022

Mobile robots have an important role in material handling manufacturing and can be used for a variety of automated tasks. The accuracy the robot’s moving trajectory has become key issue affecting its work efficiency. This paper presents method optimizing mobile robot based on digital twin robot. is created by Unity, trained virtual environment applied to physical space. simulation training provides schemes actual movement Based data returned robot, preset dynamically adjusted, which turn enables correction contribution this use genetic algorithms path planning robots, optimization reducing error through interaction real data. It map learning domain

Язык: Английский

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Multi-Scale Feature Fusion Convolutional Neural Network for Indoor Small Target Detection

Frontiers in Neurorobotics, Год журнала: 2022, Номер 16

Опубликована: Май 19, 2022

The development of object detection technology makes it possible for robots to interact with people and the environment, but changeable application scenarios make accuracy small medium objects in practical low. In this paper, based on multi-scale feature fusion indoor target method, using device collect different images angle, light, shade conditions, use image enhancement set up amplify a date set, SSD algorithm layer its adjacent features fusion. Faster R-CNN, YOLOv5, SSD, models were trained an scene data transfer learning. experimental results show that can improve all kinds objects, especially relatively scale. addition, although speed improved decreases, is faster than which better achieves balance between speed.

Язык: Английский

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Low-Illumination Image Enhancement Algorithm Based on Improved Multi-Scale Retinex and ABC Algorithm Optimization

Frontiers in Bioengineering and Biotechnology, Год журнала: 2022, Номер 10

Опубликована: Апрель 11, 2022

In order to solve the problems of poor image quality, loss detail information and excessive brightness enhancement during in low light environment, we propose a low-light algorithm based on improved multi-scale Retinex Artificial Bee Colony (ABC) optimization this paper. First all, makes two copies original image, afterwards, irradiation component is obtained by used structure extraction from texture via relative total variation for first combines it with obtain reflection which are simultaneously enhanced using histogram equalization, bilateral gamma function correction filtering. next part, second equalization edge-preserving Weighted Guided Image Filtering (WGIF). Finally, weight-optimized fusion performed ABC algorithm. The mean values Information Entropy (IE), Average Gradient (AG) Standard Deviation (SD) images respectively 7.7878, 7.5560 67.0154, improvement compared 2.4916, 5.8599 52.7553. results experiment show that proposed paper improves problem process, enhances sharpness, highlights details, restores color also reduces noise good edge preservation enables better visual perception image.

Язык: Английский

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Real-Time Target Detection Method Based on Lightweight Convolutional Neural Network

Frontiers in Bioengineering and Biotechnology, Год журнала: 2022, Номер 10

Опубликована: Авг. 16, 2022

The continuous development of deep learning improves target detection technology day by day. current research focuses on improving the accuracy technology, resulting in model being too large. number parameters and speed are very important for practical application embedded systems. This article proposed a real-time method based lightweight convolutional neural network to reduce improve speed. In this article, depthwise separable residual module is constructed combining convolution non-bottleneck-free module, structure used replace VGG backbone SSD feature extraction parameter quantity At same time, kernels 1 × 3 standard adding 1, respectively, obtain multiple graphs corresponding SSD, established integrating information graphs. self-built dataset complex scenes comparative experiments; experimental results verify effectiveness superiority method. tested video performance model, deployed Android platform scalability model.

Язык: Английский

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Fuzzy-PID-Based Atmosphere Packaging Gas Distribution System for Fresh Food

Applied Sciences, Год журнала: 2023, Номер 13(4), С. 2674 - 2674

Опубликована: Фев. 19, 2023

The regulation process of gas distribution systems for atmosphere packaging has the characteristics being nonlinear time varying and having hysteric delay. When conventional proportional-integral-derivative (PID) control algorithm is applied to this kind system, it difficult set parameters as consuming poor reliability. For these reasons, paper designs a system fresh food based on fuzzy PID controller. step response method used construct system’s mathematical model under given conditions optimize flow. A simulation experimental platform compare between controller designed, effectiveness strategy verified, which proves that can improve performance monitoring system. realize remote processes through use mobile phone communication network. data transmission reliable, operation convenient, and, at same time, overall efficiency improved. results show faster speed good environmental adaptability stability about 38 s, while 85 s. concentration error gases ±0.25% floating, accuracy increased by 12 times, 50% when stable.

Язык: Английский

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Advances in solar forecasting: Computer vision with deep learning

Advances in Applied Energy, Год журнала: 2023, Номер 11, С. 100150 - 100150

Опубликована: Авг. 7, 2023

Renewable energy forecasting is crucial for integrating variable sources into the grid. It allows power systems to address intermittency of supply at different spatiotemporal scales. To anticipate future impact cloud displacements on generated by solar facilities, conventional modeling methods rely numerical weather prediction or physical models, which have difficulties in assimilating information and learning systematic biases. Augmenting computer vision with machine overcomes some these limitations fusing real-time cover observations surface measurements acquired from multiple sources. This Review summarizes recent progress multisensor Earth a focus deep learning, provides necessary theoretical framework develop architectures capable extracting relevant data ground-level sky cameras, satellites, stations, sensor networks. Overall, has potential significantly improve accuracy robustness meteorology; however, more research realize this its limitations.

Язык: Английский

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Research on Optimization of Diesel Engine Speed Control Based on UKF-Filtered Data and PSO Fuzzy PID Control

Processes, Год журнала: 2025, Номер 13(3), С. 777 - 777

Опубликована: Март 7, 2025

With the continuous development of industrial automation, diesel engines play an increasingly important role in various types construction machinery and power generation equipment. Improving dynamic static performance speed control system single-cylinder can not only significantly improve efficiency equipment, but also effectively reduce energy consumption emissions. Particle swarm optimization (PSO) fuzzy PID algorithms have been widely used many complex engineering problems due to their powerful global capability excellent adaptability. Currently, PSO-based research mainly integrates hybrid algorithmic strategies avoid local optimum problem, lacks noise suppression input error rate change error. This makes algorithm susceptible coupling uncertainty measurement disturbances during parameter process, leading degradation. For this reason, study proposes a new framework based on synergistic untraceable Kalman filter (UKF) PSO for engine. A PSO-optimized controller is designed by obtaining accurate estimation data using UKF. The capable quickly adjusting parameters so as alleviate nonlinearity operation engines. By establishing Matlab/Simulink simulation model, engine step response experiments (i.e., startup experiments) load mutation were carried out, process imposed. results show that optimized able overshoot 76%, shorten regulation time 58%, reduction 25% compared with conventional control. Compared without UKF reduction, scheme reduces 20%, shortens 48%, improves effect 23%. method integrated has superior terms stability accuracy. responsiveness speed, achieves better control, provides useful reference other systems. In addition, establishes GT-POWER model 168 F engine, compares cylinder pressure fuel under four operating conditions through bench tests ensure physical reasonableness kinetic distorted front-end model.

Язык: Английский

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A Tandem Robotic Arm Inverse Kinematic Solution Based on an Improved Particle Swarm Algorithm

Frontiers in Bioengineering and Biotechnology, Год журнала: 2022, Номер 10

Опубликована: Май 19, 2022

The analysis of robot inverse kinematic solutions is the basis control and path planning, great importance for research. Due to limitations analytical geometric methods, intelligent algorithms are more advantageous because they can obtain approximate directly from robot's positive equations, saving a large number computational steps. Particle Swarm Algorithm (PSO), as one algorithms, widely used due its simple principle excellent performance. In this paper, we propose an improved particle swarm algorithm kinematics solving. Since setting weights affects global local search ability algorithm, paper proposes adaptive weight adjustment strategy improving ability. Considering running time condition based on limit joints, introduces position coefficient k in velocity factor. Meanwhile, exponential product form modeling method (POE) spinor theory chosen. Compared with traditional DH method, approach describes motion rigid body whole avoids singularities that arise when described by coordinate system. order illustrate advantages terms accuracy, time, convergence adaptability, three experiments were conducted general six-degree-of-freedom industrial robotic arm, PUMA560 arm seven-degree-of-freedom research objects. all experiments, parameters range joint angles, initial attitude end-effector given, impact point set verify whether angles found reach specified positions. Experiments 2 3, proposed compared (PSO) quantum (QPSO) direction solving operation convergence. results show other two ensure higher accuracy orientation end-effector. error 0 maximum 1.29 × 10-8. while minimum -1.64 10-5 -4.03 10-6. has shorter algorithms. last computing 0.31851 0.30004s respectively, shortest 0.33359 0.30521s respectively. convergence, achieve faster stable than After changing experimental subjects, still maintains which indicates applicable certain potential multi-arm solution. This provides new way thinking solution problem.

Язык: Английский

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Time Optimal Trajectory Planing Based on Improved Sparrow Search Algorithm

Frontiers in Bioengineering and Biotechnology, Год журнала: 2022, Номер 10

Опубликована: Март 22, 2022

Complete trajectory planning includes path planning, inverse solution solving and optimization. In this paper, a highly smooth time-saving approach to is obtained by improving the kinematic optimization algorithms for time-optimal problem. By partitioning joint space, paper obtains an calculation based on of saving 40% kinematics time. This means that large number computational resources can be saved in planning. addition, improved sparrow search algorithm (SSA) proposed complete trajectory. A Tent chaotic mapping was used optimize way generating initial populations. The further combining it with adaptive step factor. experiments demonstrated performance SSA. robot’s optimized time algorithm. Experimental results show method improve convergence speed global capability ensure trajectories.

Язык: Английский

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Intelligent Detection of Steel Defects Based on Improved Split Attention Networks

Frontiers in Bioengineering and Biotechnology, Год журнала: 2022, Номер 9

Опубликована: Янв. 13, 2022

The intelligent monitoring and diagnosis of steel defects plays an important role in improving quality, production efficiency, associated smart manufacturing. application the bio-inspired algorithms to mechanical engineering problems is great significance. split attention network improvement residual network, it visual mechanism bionic algorithm. In this paper, based on feature pyramid improved optimised terms data enhancement, multi-scale fusion structure optimisation. DF-ResNeSt50 model proposed, which introduces a simple modularized block, can improve cross-feature graph groups. Finally, experimental validation proves that proposed has good performance prospects detection defects.

Язык: Английский

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