Applied Sciences

Research

43 pages, 8806 KiB

Open AccessArticle

A Study on the Design and Control of the Overhead Hoist Railway-Based Transportation System

by Thuy Duy Truong, Xuan Tuan Nguyen, Tuan Anh Vu, Nguyen Huu Loc Khuu, Quoc Dien Le, Tran Thanh Cong Vu, Hoa Binh Tran and Tuong Quan Vo

Appl. Sci. 2023, 13(17), 9985; https://doi.org/10.3390/app13179985 - 4 Sep 2023

Cited by 3 | Viewed by 3213

Abstract

Overhead hoist transportation systems (OHTS) have been the subject of worldwide research and development in recent years. The majority of these systems are utilized in semi-automated or fully automated factories. This article proposes a new solution for OTHS based on the concept of [...] Read more.

Overhead hoist transportation systems (OHTS) have been the subject of worldwide research and development in recent years. The majority of these systems are utilized in semi-automated or fully automated factories. This article proposes a new solution for OTHS based on the concept of the modulation of mobile units that can move on a railway structure from one point to another. The OHTS mentioned in this article is a group of shuttles that can operate independently but which also have the ability to cooperate together to complete the desired tasks. By using the space below the ceiling, this system can operate without affecting the original design of the factories. There are many potential fields of application for picking-up and delivering, such as the medical field, the food and beverage fields, automotive and electrical appliances, etc. Moreover, by applying Dijkstra’s algorithm in the controller design, the transportation speed among the stations in the whole system can be improved. The real prototype of the whole system, including three shuttles, is also manufactured to explore and assess the design and operation of the proposed system and its controller. Full article

(This article belongs to the Special Issue Recent Advances in Autonomous Systems and Robotics)

► Show Figures

Figure 1

19 pages, 6716 KiB

Open AccessArticle

A Method for Extracting a Laser Center Line Based on an Improved Grayscale Center of Gravity Method: Application on the 3D Reconstruction of Battery Film Defects

by Rongbin Yao, Baiyi Wang, Mengya Hu, Dezheng Hua, Lequn Wu, He Lu and Xinhua Liu

Appl. Sci. 2023, 13(17), 9831; https://doi.org/10.3390/app13179831 - 30 Aug 2023

Cited by 4 | Viewed by 2394

Abstract

Extraction of the laser fringe center line is a key step in the 3D reconstruction of linear structured light, the accuracy of which is directly related to the quality of the 3D model. A laser center line extraction method based on an improved [...] Read more.

Extraction of the laser fringe center line is a key step in the 3D reconstruction of linear structured light, the accuracy of which is directly related to the quality of the 3D model. A laser center line extraction method based on an improved gray center of gravity method is proposed to solve the problem of low extraction accuracy. Firstly, a smoothing method is used to eliminate the flat top of the laser line, and the Gaussian curve is adopted to fit the peak position of the curve. Then, the gray threshold is set to automatically extract the laser linewidth, and based on the window opening, the grayscale center of gravity method is improved to extract the coordinates of the center pixel for the second time. Finally, experiments show that the average absolute error of the improved laser line extraction method is 0.026 pixels, which is 2.3 times lower than the gray center of gravity method, 1.9 times lower than the curve fitting method, and the standard error can reach 0.005 pixels. Compared with the gray center of gravity method and the curve fitting method, the influence of gray value change on the center line extraction is more fully considered, and the center of the light strip can be extracted more accurately, achieving sub-pixel accuracy. Full article

(This article belongs to the Special Issue Recent Advances in Autonomous Systems and Robotics)

► Show Figures

Figure 1

15 pages, 6068 KiB

Open AccessArticle

Optimization of Wheelchair-Mounted Robotic Arms’ Base Placement by Fusing Occupied Grid Map and Inverse Reachability Map

by Ming Zhong, Yuhang He, Yan Liu, Ruiqing Han and Yaxin Liu

Appl. Sci. 2023, 13(14), 8510; https://doi.org/10.3390/app13148510 - 23 Jul 2023

Cited by 1 | Viewed by 1791

Abstract

In a household setting, a wheelchair-mounted robotic arm (WMRA) can be useful for assisting elderly and disabled individuals. However, the current WMRA can only perform movement and grasping tasks through joystick remote control. This method results in low efficiency due to poor coordination [...] Read more.

In a household setting, a wheelchair-mounted robotic arm (WMRA) can be useful for assisting elderly and disabled individuals. However, the current WMRA can only perform movement and grasping tasks through joystick remote control. This method results in low efficiency due to poor coordination between the mobile platform and the robotic arm as well as the numerous operational steps required. To improve the efficiency and success rate of the robot in task execution, this paper proposes a parking location optimization method that combines the occupied grid map (OGM) and the inverse reachability map (IRM). Firstly, the SLAM algorithm is used to collect environment information, which is then stored in the form of an occupied grid map. The robotic arm workspace is then gridded, and the inverse reachability map is calculated based on the grasping pose of the target object. Finally, the optimal position of the mobile platform is obtained by comparing the optimal location point in the inverse reachability map and the obstacle information in the occupied grid map. This process achieves base placement optimization based on the grasping pose. The experimental results demonstrate that this method reduces the user operation time by 97.31% and overall task completion time by 40.57% when executing household environment tasks compared with the joystick control, increasing the range of executable tasks compared with the algorithm of the EL-E robot and reducing task completion time by 23.48% for the same task. This paper presents a parking location optimization method that can improve the grasping efficiency of the robotic arm and achieve parking location position selection for the WMRA in a household environment. Full article

(This article belongs to the Special Issue Recent Advances in Autonomous Systems and Robotics)

► Show Figures

Figure 1

17 pages, 4656 KiB

Open AccessArticle

Optimization of Vehicle Powertrain Mounting System Based on Generalized Inverse Cascade Method under Uncertainty

by Yongbo Shui, Hansheng Wen, Jian Zhao, Yudong Wu and Haibo Huang

Appl. Sci. 2023, 13(13), 7615; https://doi.org/10.3390/app13137615 - 28 Jun 2023

Cited by 3 | Viewed by 2447

Abstract

This paper presents a summary of the optimization design process for a multi-objective, two-level engineering problem, utilizing the generalized inverse cascade method under uncertainty. The primary objective is to enhance the vibration isolation performance of a mounting system, considering the influence of uncertain [...] Read more.

This paper presents a summary of the optimization design process for a multi-objective, two-level engineering problem, utilizing the generalized inverse cascade method under uncertainty. The primary objective is to enhance the vibration isolation performance of a mounting system, considering the influence of uncertain factors on its stiffness. The focus is on determining the value range of the design variables at the bottom layer, ensuring that the design goal is met with a specified confidence level. To illustrate the application of this methodology, the optimization design of a powertrain mount is used as a case study. A data-driven approach is adopted, establishing a quantitative mapping relationship between mount stiffness, force transmission rate, modal decoupling rate, and other design indicators. This is achieved through the development of a CRBM-DBN approximate model, which combines Conditional Restricted Boltzmann Machines (CRBMs) and a Deep Belief Network (DBN). Additionally, an intelligent optimization algorithm and interval search technology are employed to determine the optimal design interval for the mount stiffness. Simulation and experimental verification are conducted using selected parameter combinations. The results demonstrate notable improvements in the vibration isolation performance, modal decoupling rate, and vehicle NVH performance when compared to the original state. These findings provide valuable insights for the interval optimization design of similar multi-objective, as well as two-level engineering problems, serving as useful references for future research and applications. Full article

(This article belongs to the Special Issue Recent Advances in Autonomous Systems and Robotics)

► Show Figures

Figure 1

20 pages, 4143 KiB

Open AccessArticle

Façade Protrusion Recognition and Operation-Effect Inspection Methods Based on Binocular Vision for Wall-Climbing Robots

by Ming Zhong, Ye Ma, Zhan Li, Jiajian He and Yaxin Liu

Appl. Sci. 2023, 13(9), 5721; https://doi.org/10.3390/app13095721 - 5 May 2023

Cited by 4 | Viewed by 2003

Abstract

The cleaning and maintenance of large-scale façades is a high-risk industry. Although existing wall-climbing robots can replace humans who work on façade surfaces, it is difficult for them to operate on façade protrusions due to a lack of perception of the surrounding environment. [...] Read more.

The cleaning and maintenance of large-scale façades is a high-risk industry. Although existing wall-climbing robots can replace humans who work on façade surfaces, it is difficult for them to operate on façade protrusions due to a lack of perception of the surrounding environment. To address this problem, this paper proposes a binocular vision-based method to assist wall-climbing robots in performing autonomous rust removal and painting. The method recognizes façade protrusions through binocular vision, compares the recognition results with an established dimension database to obtain accurate information on the protrusions and then obtains parameters from the process database to guide the operation. Finally, the robot inspects the operation results and dynamically adjusts the process parameters according to the finished results, realizing closed-loop feedback for intelligent operation. The experimental results show that the You Only Look Once version 5 (YOLOv5) recognition algorithm achieves a 99.63% accuracy for façade protrusion recognition and a 93.33% accuracy for the detection of the rust removal effect using the histogram comparison method. The absolute error of the canny edge detection algorithm is less than 3 mm and the average relative error is less than 2%. This paper establishes a vision-based façade operation process with good inspection effect, which provides an effective vision solution for the automation operation of wall-climbing robots on the façade. Full article

(This article belongs to the Special Issue Recent Advances in Autonomous Systems and Robotics)

► Show Figures

Figure 1

20 pages, 6836 KiB

Open AccessArticle

Dynamic Scheduling and Optimization of AGV in Factory Logistics Systems Based on Digital Twin

by Shiqing Wu, Wenting Xiang, Weidong Li, Long Chen and Chenrui Wu

Appl. Sci. 2023, 13(3), 1762; https://doi.org/10.3390/app13031762 - 30 Jan 2023

Cited by 16 | Viewed by 5957

Abstract

At present, discrete workshops demand higher transportation efficiency, but the traditional scheduling strategy of the logistics systems can no longer meet the requirements. In a transportation system with multiple automated guided vehicles (multi-AGVs), AGV path conflicts directly affect the efficiency and coordination of [...] Read more.

At present, discrete workshops demand higher transportation efficiency, but the traditional scheduling strategy of the logistics systems can no longer meet the requirements. In a transportation system with multiple automated guided vehicles (multi-AGVs), AGV path conflicts directly affect the efficiency and coordination of the whole system. At the same time, the uncertainty of the number and speed of AGVs will lead to excessive cost. To solve these problems, an AGVs Multi-Objective Dynamic Scheduling (AMODS) method is proposed which is based on the digital twin of the workshop. The digital twin of the workshop is built in the virtual space, and a two-way exchange and real-time control framework based on dynamic data is established. The digital twin system is adopted to exchange data in real time, create a real-time updated dynamic task list, determine the number of AGVs and the speed of AGVs under different working conditions, and effectively improve the efficiency of the logistics system. Compared with the traditional scheduling strategy, this paper is of practical significance for the scheduling of the discrete workshop logistics systems to improve the production efficiency, utilization rate of resources, and dynamic response capability. Full article

(This article belongs to the Special Issue Recent Advances in Autonomous Systems and Robotics)

► Show Figures

Figure 1

21 pages, 6384 KiB

Open AccessArticle

A Novel Pressure Relief Hole Recognition Method of Drilling Robot Based on SinGAN and Improved Faster R-CNN

by Bin Liang, Zhongbin Wang, Lei Si, Dong Wei, Jinheng Gu and Jianbo Dai

Appl. Sci. 2023, 13(1), 513; https://doi.org/10.3390/app13010513 - 30 Dec 2022

Cited by 6 | Viewed by 1945

Abstract

The drilling robot is the key equipment for pressure relief in rockburst mines, and the accurate recognition of a pressure relief hole is the premise for optimizing the layout of pressure relief holes and intelligent drilling. In view of this, a pressure relief [...] Read more.

The drilling robot is the key equipment for pressure relief in rockburst mines, and the accurate recognition of a pressure relief hole is the premise for optimizing the layout of pressure relief holes and intelligent drilling. In view of this, a pressure relief hole recognition method for a drilling robot, based on single-image generative adversarial network (SinGAN) and improved faster region convolution neural network (Faster R-CNN), is proposed. Aiming at the problem of insufficient sample generation diversity and poor performance of the traditional SinGAN model, some improvement measures including image size adjustment, multi-stage training, and dynamically changing iteration times are designed as an improved SinGAN for the generation of pressure relief hole images. In addition, to solve the problem that the traditional depth neural network is not ideal for small-size target recognition, an improved Faster R-CNN based on multi-scale image input and multi-layer feature fusion is designed with the improved SqueezeNet as the framework, and the sample data collected from ground experiments are used for comparative analysis. The results indicate that the improved SinGAN model can improve the diversity of generated images on the premise of ensuring the quality of image samples, and can greatly improve the training speed of the model. The accuracy and recall rate of the improved Faster R-CNN model were able to reach 90.09% and 98.32%, respectively, and the average detection time was 0.19 s, which verifies the superiority of the improved Faster R-CNN model. To further verify the practicability of the proposed method, some field images were collected from the underground rockburst relief area in the coal mine, and a corresponding test analysis was carried out. Compared with three YOLO models, the accuracy and recall rate of improved Faster R-CNN model improved significantly, although the training time and recognition time increased to a certain extent, which proves the feasibility and effectiveness of the proposed method. Full article

(This article belongs to the Special Issue Recent Advances in Autonomous Systems and Robotics)

► Show Figures

Figure 1

13 pages, 6022 KiB

Open AccessArticle

Prediction of Ride Comfort of High-Speed Trains Based on Train Seat–Human Body Coupled Dynamics Model

by Heng Li, Xu Zheng, Wenqiang Dai and Yi Qiu

Appl. Sci. 2022, 12(24), 12900; https://doi.org/10.3390/app122412900 - 15 Dec 2022

Cited by 4 | Viewed by 2411

Abstract

A train seat–human body coupled dynamics model was established to predict the ride comfort of high-speed trains. The train and track and the seat and human body were both coupled in the model. An on-site vibration experiment in a high-speed train was carried [...] Read more.

A train seat–human body coupled dynamics model was established to predict the ride comfort of high-speed trains. The train and track and the seat and human body were both coupled in the model. An on-site vibration experiment in a high-speed train was carried out to calibrate each part of the train seat–human body coupled dynamics model. Based on the evaluation method proposed by BS EN 12299:2009, the distribution of ride comfort in the carriage and the effect of seat cushion stiffness and damping on ride comfort were analyzed systematically. The results showed that the seats in the middle of the carriage had the best comfort performance, while those near the side wall and close to the position where the suspension force of the second series was acting were less comfortable. The seat cushion stiffness and damping had great effect on ride comfort. Full article

(This article belongs to the Special Issue Recent Advances in Autonomous Systems and Robotics)

► Show Figures

Figure 1

Journal Menu

Journal Browser

Recent Advances in Autonomous Systems and Robotics

Share This Special Issue

Special Issue Editors

Special Issue Information

Keywords

Benefits of Publishing in a Special Issue

Published Papers (8 papers)

Research

Further Information

Guidelines

MDPI Initiatives

Follow MDPI