Manipulator trajectory tracking based on adaptive sliding mode control DOI
Haoyi Zhao, Bo Tao, Ruyi Ma

et al.

Concurrency and Computation Practice and Experience, Journal Year: 2022, Volume and Issue: 34(21)

Published: May 24, 2022

Abstract A manipulator is a complex electromechanical system that nonlinear, strongly coupled, and uncertain. Achieving its precise high‐quality trajectory control difficult. Sliding mode (SMC) one of the common methods for manipulators. However, discontinuities in SMC can cause jitter vibration system, leading to reduction performance system. For self‐adaptive capability problem SMC, Dobot magician treated as research object this article. The dynamics equations are established by Lagrange method, simplified model constructed. method sliding proposed. Self‐adaptive parameters added achieve adjustment parameters. In MATLAB/Simulink simulation environment analysis show has better self‐tuning ability tracking than traditional weakens phenomenon existing SMC.

Language: Английский

Genetic Algorithm-Based Trajectory Optimization for Digital Twin Robots DOI Creative Commons
Xin Liu, Du Jiang, Bo Tao

et al.

Frontiers in Bioengineering and Biotechnology, Journal Year: 2022, Volume and Issue: 9

Published: Jan. 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

Language: Английский

Citations

113
Multi-Scale Feature Fusion Convolutional Neural Network for Indoor Small Target Detection DOI Creative Commons
Li Huang, Cheng Chen, Juntong Yun

et al.

Frontiers in Neurorobotics, Journal Year: 2022, Volume and Issue: 16

Published: May 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.

Language: Английский

Citations

97
Self-Tuning Control of Manipulator Positioning Based on Fuzzy PID and PSO Algorithm DOI Creative Commons
Ying Liu, Du Jiang, Juntong Yun

et al.

Frontiers in Bioengineering and Biotechnology, Journal Year: 2022, Volume and Issue: 9

Published: Feb. 11, 2022

With the manipulator performs fixed-point tasks, it becomes adversely affected by external disturbances, parameter variations, and random noise. Therefore, is essential to improve robust accuracy of controller. In this article, a self-tuning particle swarm optimization (PSO) fuzzy PID positioning controller designed based on control. The quantization scaling factors in algorithm are optimized PSO order achieve high robustness manipulator. First all, mathematical model developed, designed. A PD control strategy with compensation for gravity used system. Then, parameters dynamically minute-tuned 1. Through closed-loop loop adjust magnitude factors–proportionality online. Correction values outputted modified 2. factor–proportion factor online achieved find optimal Finally, performance improved verified simulation environment. results show that transient response speed, tracking accuracy, follower characteristics system significantly improved.

Language: Английский

Citations

95
Low-Illumination Image Enhancement Algorithm Based on Improved Multi-Scale Retinex and ABC Algorithm Optimization DOI Creative Commons
Ying Sun, Zichen Zhao, Du Jiang

et al.

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

Published: April 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.

Language: Английский

Citations

83
Real-Time Target Detection Method Based on Lightweight Convolutional Neural Network DOI Creative Commons
Juntong Yun, Du Jiang, Ying Liu

et al.

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

Published: Aug. 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.

Language: Английский

Citations

73
Time Optimal Trajectory Planing Based on Improved Sparrow Search Algorithm DOI Creative Commons
Xiaofeng Zhang, Fan Xiao, Xiliang Tong

et al.

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

Published: March 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.

Language: Английский

Citations

58
Intelligent Detection of Steel Defects Based on Improved Split Attention Networks DOI Creative Commons

Zhiqiang Hao,

Zhigang Wang, Dongxu Bai

et al.

Frontiers in Bioengineering and Biotechnology, Journal Year: 2022, Volume and Issue: 9

Published: Jan. 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.

Language: Английский

Citations

57
Path Planning Optimization of Intelligent Vehicle Based on Improved Genetic and Ant Colony Hybrid Algorithm DOI Creative Commons

Kangjing Shi,

Li Huang, Du Jiang

et al.

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

Published: July 1, 2022

Intelligent vehicles were widely used in logistics handling, agriculture, medical service, industrial production, and other industries, but they often not smooth enough planning the path, number of turns was large, resulting high energy consumption. Aiming at unsmooth path problem four-wheel intelligent vehicle algorithm, this article proposed an improved genetic ant colony hybrid physical model established. This first optimization algorithm about heuristic function with adaptive change evaporation factor. Then, it on fitness function, adjustment crossover factor, mutation Last, addition a deletion operator, adoption elite retention strategy, suboptimal solutions obtained from to obtain optimized new populations. The simulation environment for is windows 10, processor Intel Core i5-5257U, running memory 4GB, compilation MATLAB2018b, samples 50, maximum iterations 100, initial population size 200, 50. Simulation experiments show that effective. Compared traditional reduced by 46% average 75% simple grid. 47% 21% complex works better reduce maps.

Language: Английский

Citations

49
Grasping Pose Detection for Loose Stacked Object Based on Convolutional Neural Network With Multiple Self-Powered Sensors Information DOI
Juntong Yun, Du Jiang,

Ying Sun

et al.

IEEE Sensors Journal, Journal Year: 2022, Volume and Issue: 23(18), P. 20619 - 20632

Published: Aug. 5, 2022

There are a variety of objects, random postures and multiple objects stacked in disorganized manner unstructured home applications, which leads to the object grasping posture estimation planning based on machine vision become very complicated. This paper proposes method cluttering pose detection convolutional neural network with self-powered sensors information. Firstly, search strategy for candidate poses 3D point cloud is proposed, single-channel image dataset representing this established by using Bigbird dataset. Secondly, ResNet constructed rank filter single channel captured images bit pose. It also compared three mainstream classification networks, Inception V2, VGG-A LetNet, perception analysis function execution developed under ROS. The effective manipulator scene scattered piles realized results position combined information sensors, other networks. In environment experiment show that superior average success rate ResNet, InceptionV2, VGGA LetNet networks 90.67%, 82.67%, 86.67% 87.33% respectively, verifies effectiveness superiority deep learn-based model proposed paper.

Language: Английский

Citations

47
Attitude Stabilization Control of Autonomous Underwater Vehicle Based on Decoupling Algorithm and PSO-ADRC DOI Creative Commons
Xiong Wu, Du Jiang, Juntong Yun

et al.

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

Published: Feb. 28, 2022

Autonomous Underwater Vehicle are widely used in industries, such as marine resource exploitation and fish farming, but they often subject to a large amount of interference which cause poor control stability, while performing their tasks. A decoupling algorithm is proposed single volume-single attitude angle model constructed for the problem severe coupling system six degrees freedom Vehicle. Aiming at complex Active Disturbance Rejection Control (ADRC) adjustment relying on manual experience, PSO-ADRC realize automatic its parameters, improves anti-interference ability accuracy dynamic environment. The method were verified through experiments.

Language: Английский

Citations

46