2023 International Conference on Robotics and Automation in Industry (ICRAI)最新文献_第4页

An Improved Cooperative Spectrum Sensing Scheme for Emulation Attacker Detection in Cognitive Radio Network 一种改进的认知无线网络仿真攻击检测协同频谱感知方案

2023 International Conference on Robotics and Automation in Industry (ICRAI) Pub Date : 2023-03-03 DOI: 10.1109/ICRAI57502.2023.10089590

Momin Nadeem Awan, S. Haq, S. Anwar

引用次数: 0

Comparison Between ANSYS Fluent and Solidworks Internal Flow Simulation for Analysis of A Fuzzy Logic Controller-Based Heating/Cooling System in A Mobile Robot Design 基于模糊逻辑控制器的移动机器人冷热系统设计中ANSYS Fluent与Solidworks内部流场仿真的比较

2023 International Conference on Robotics and Automation in Industry (ICRAI) Pub Date : 2023-03-03 DOI: 10.1109/ICRAI57502.2023.10089571

M. Afaq, R. Ahmad

{"title":"Comparison Between ANSYS Fluent and Solidworks Internal Flow Simulation for Analysis of A Fuzzy Logic Controller-Based Heating/Cooling System in A Mobile Robot Design","authors":"M. Afaq, R. Ahmad","doi":"10.1109/ICRAI57502.2023.10089571","DOIUrl":"https://doi.org/10.1109/ICRAI57502.2023.10089571","url":null,"abstract":"Nowadays, Computational Fluid Dynamics (CFD) software's have become important tools to study the behavior of fluids in the design phase of robots in various applications. This includes fluid behavior around underwater remotely operated vehicles, aerodynamic characteristics of mobile robots/drones in extreme outdoor environments, and internal flow simulation to determine the heating/cooling time of an enclosed space and estimate the system's energy requirements. For this paper, two CFD software's; ANSYS Fluent and Solidworks 2022 are used to conduct a CFD analysis on the heating/cooling of the internal space of a mobile robot design aimed to operate in extreme temperatures ranging from −40 °C to 50 °C. Heating time is determined by using a constant power magnitude of 8138683 W/m3 emitted from four different heating elements located at different parts of the robot body and two fans rotating at 1800 rpm. Moreover, the cooling time of the internal space is evaluated based on fans operating at 6000 rpm over the electronics and three outlets that direct the warm air to the outside environment. For both software's, the same boundary conditions were applied to the robot body to obtain fair results for comparison. Based on the simulation results, the desired temperature of 8 °C from an initial temperature of −40 °C was reached within 44 s for ANSYS Fluent and 650 s for Solidworks. For cooling, 8 °C was obtained within 6 s for ANSYS Fluent and 24 s for Solidworks. The difference in the results between the two software's is mainly due to the method in which the fluid domain is defined. In the case of Solidworks, it considers the material thickness on the boundary between solid/fluid regions.","PeriodicalId":447565,"journal":{"name":"2023 International Conference on Robotics and Automation in Industry (ICRAI)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121774756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Autonomous Navigation and Mapping of Water Channels in a Simulated Environment Using Micro-Aerial Vehicles 利用微型飞行器在模拟环境中自主导航和绘制水道

2023 International Conference on Robotics and Automation in Industry (ICRAI) Pub Date : 2023-03-03 DOI: 10.1109/ICRAI57502.2023.10089599

Syed Izzat Ullah, Abubakr Muhammad

{"title":"Autonomous Navigation and Mapping of Water Channels in a Simulated Environment Using Micro-Aerial Vehicles","authors":"Syed Izzat Ullah, Abubakr Muhammad","doi":"10.1109/ICRAI57502.2023.10089599","DOIUrl":"https://doi.org/10.1109/ICRAI57502.2023.10089599","url":null,"abstract":"Irrigation canal networks serve as the bedrock of agriculture sectors across the globe as they are the primary channel through which water runs from major sources to agricultural lands. However, the water-carrying capacity of these water channels significantly reduces over time because of erosion, structural deterioration, and silt accumulation. As a result, routine inspections are required to analyze and repair these water channels which necessitates automation because of the vast length of the channels. We present a framework that enables Micro-Aerial Vehicles(MAVs) not only to navigate in an unknown cluttered canal environment but also to provide a complete 3-Dimensional map for the inspection. The framework consists of three main components (mapping, path planning, and mission planner) that gradually explore the environment while solving for start to local goal queries. We use Octomap; an octree-based representation of the environment for mapping, and we extended the Informed Rapidly-exploring Random Tree (Informed-RRT*) for optimal path planning and replan paths with respect to the static nearby and dynamic obstacles perceived during the execution of the mission. A simulated 2,378 meters length of canal environment is implemented and demonstrated by using the Airsim simulation in the Unreal engine, running on Robot Operation System (ROS) and Linux OS. Results obtained show that the framework enables the MAV to navigate over a simulated canal environment and allows the MAV to map the 3D structure of the canal.","PeriodicalId":447565,"journal":{"name":"2023 International Conference on Robotics and Automation in Industry (ICRAI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130610409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Video Stabilization using RAFT-based Optical Flow 基于raft光流的视频防抖

2023 International Conference on Robotics and Automation in Industry (ICRAI) Pub Date : 2023-03-03 DOI: 10.1109/ICRAI57502.2023.10089609

Rana Ashar, Burhan A. Sadiq, Hira Mohiuddin, Saniya Ashraf, Muhammad Imran, A. Ullah

引用次数: 0

Design and Adaptive Compliance Control of a Wearable Walk Assist Device 一种可穿戴行走辅助装置的设计与自适应顺应控制

2023 International Conference on Robotics and Automation in Industry (ICRAI) Pub Date : 2023-03-03 DOI: 10.1109/ICRAI57502.2023.10089580

S. H. Shah, M. S. Alam, Muhammad Arsalan, Izhar ul Haq, S. G. Khan, J. Iqbal

{"title":"Design and Adaptive Compliance Control of a Wearable Walk Assist Device","authors":"S. H. Shah, M. S. Alam, Muhammad Arsalan, Izhar ul Haq, S. G. Khan, J. Iqbal","doi":"10.1109/ICRAI57502.2023.10089580","DOIUrl":"https://doi.org/10.1109/ICRAI57502.2023.10089580","url":null,"abstract":"The ability to walk independently is a predominant feature that human beings are bestowed with by nature. People with moving disabilities face many challenges in day-to-day activities and they have to rely on others to perform their day-to-day activities. Robotic walk-assist technology has the ability to play an indispensable role in improving the mobility of people who are suffering from walking disabilities. However, there are several technical challenges, such as safe interaction of human and robotic walk-assist devices, and control of highly nonlinear dynamic systems. This paper proposes a preliminary design of an assistive device for elderly persons having poor mobility. An adaptive inertia-related controller is employed for the desired tracking control of hip and knee joints of the walk assist device. The mass estimation of both hip and knee links is estimated through the proposed adaptive controller, which plays an important role if people of different weights and sizes opt to use the same device. Moreover, the adaptive control scheme is coupled with a compliant spring-mass-damper reference model to realize a compliance control for the hip and knee joints of the exoskeleton wearable walk-assist robotic device. Simulation results validate the performance of the proposed controller for both hip and knee joints. Results demonstrate that proposed controller has the capability to estimate the weights of the links, and the uncertain parameters while changing the assistive device dynamics.","PeriodicalId":447565,"journal":{"name":"2023 International Conference on Robotics and Automation in Industry (ICRAI)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121004294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Genetic Drift and its Effects on the Performance of Genetic Algorithm(GA) 遗传漂变及其对遗传算法性能的影响

2023 International Conference on Robotics and Automation in Industry (ICRAI) Pub Date : 2023-03-03 DOI: 10.1109/ICRAI57502.2023.10089573

Sami Ullah, M. Masood

{"title":"Genetic Drift and its Effects on the Performance of Genetic Algorithm(GA)","authors":"Sami Ullah, M. Masood","doi":"10.1109/ICRAI57502.2023.10089573","DOIUrl":"https://doi.org/10.1109/ICRAI57502.2023.10089573","url":null,"abstract":"A genetic algorithm (GA) is a meta-heuristic computation method that is inspired by Darwin's theory of evolution. GA has a promising future in optimization and search problems. It has caught the interest of researchers in the fields of data science, artificial intelligence, and mathematics among many others. GA depends on various operators which include parent selection, crossover, and mutation. The crossover and mutation operators incorporate diversity in the population. GA has a dependency on genetic diversity just like thriving species of any habitat. In the natural world, isolated species and small populations amplify genetic drift, increasing their chances of loss of alleles including beneficial ones. Existing research in GA has an emphasis on natural selection, however, another mechanism of evolution i.e., Genetic drift is not studied in GA. Genetic drift, like in nature, also affects genetic algorithms as it mimics natural processes. Genetic drift causes fixation of alleles and loss of diversity, making GA provide a sub-optimal solution. This research establishes the negative effects of demographic restrictions on the population as observed in the natural world. Subsequently establishes a link between research in biodiversity and evolution in the natural world to enhance the performance of GA in the digital world.","PeriodicalId":447565,"journal":{"name":"2023 International Conference on Robotics and Automation in Industry (ICRAI)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114793714","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Crop Type Classification using Multi-temporal Sentinel-2 Satellite Imagery: A Deep Semantic Segmentation Approach 基于多时相Sentinel-2卫星图像的作物类型分类:一种深度语义分割方法

2023 International Conference on Robotics and Automation in Industry (ICRAI) Pub Date : 2023-03-03 DOI: 10.1109/ICRAI57502.2023.10089586

Asim Khan, Zuhair Zafar, M. Shahzad, K. Berns, M. Fraz

{"title":"Crop Type Classification using Multi-temporal Sentinel-2 Satellite Imagery: A Deep Semantic Segmentation Approach","authors":"Asim Khan, Zuhair Zafar, M. Shahzad, K. Berns, M. Fraz","doi":"10.1109/ICRAI57502.2023.10089586","DOIUrl":"https://doi.org/10.1109/ICRAI57502.2023.10089586","url":null,"abstract":"Crop Type classification using Semantic Segmentation and remote sensing data is an important tool for decision-making related to precision agriculture. Such classification remains an unsolved challenge due to the choice of landscape, processing methodology and selected satellite imagery and its optical features, and most importantly the availability and usage of such datasets in a developing country like Pakistan. State-of-the-art semantic segmentation models lack in processing the temporal dimension of time series imagery and evident solution to process multi-spectral bands available in the satellite imagery. We propose a methodology to overcome these shortcomings by selecting appropriate band combinations for crop type classification and treating time series visual data as a single image. The proposed methodology is evaluated on the data set of six different crops collected from National Agriculture Research Center (NARC) Islamabad. The experimental results yield 85% accuracy for classifying various crop types based on the evaluation of five different semantic segmentation models. The code and the trained models are available at https://github.com/asimniazi63/crop-type-narc for other researchers working in the same domain.","PeriodicalId":447565,"journal":{"name":"2023 International Conference on Robotics and Automation in Industry (ICRAI)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122276197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Improving Popular Textbook Recursive Algorithms with Tail Recursion 用尾递归改进常用教材递归算法

2023 International Conference on Robotics and Automation in Industry (ICRAI) Pub Date : 2023-03-03 DOI: 10.1109/ICRAI57502.2023.10089594

Sami Ullah

引用次数: 0

Detection of Grape Clusters in Images Using Convolutional Neural Network 利用卷积神经网络检测图像中的葡萄簇

2023 International Conference on Robotics and Automation in Industry (ICRAI) Pub Date : 2023-03-03 DOI: 10.1109/ICRAI57502.2023.10089582

M. Shahzad, A. B. Aqeel, W. S. Qureshi

{"title":"Detection of Grape Clusters in Images Using Convolutional Neural Network","authors":"M. Shahzad, A. B. Aqeel, W. S. Qureshi","doi":"10.1109/ICRAI57502.2023.10089582","DOIUrl":"https://doi.org/10.1109/ICRAI57502.2023.10089582","url":null,"abstract":"Convolutional Neural Networks and Deep Learning have revolutionized every field since their inception. Agriculture has also been reaping the fruits of developments in mentioned fields. Technology is being revolutionized to increase yield, save water wastage, take care of diseased weeds, and also increase the profit of farmers. Grapes are among the highest profit-yielding and important fruit related to the juice industry. Pakistan being an agricultural country, can widely benefit by cultivating and improving grapes per hectare yield. The biggest challenge in harvesting grapes to date is to detect their cluster successfully; many approaches tend to answer this problem by harvest and sort technique where the foreign objects are separated later from grapes after harvesting them using an automatic harvester. Currently available systems are trained on data that is from developed or grape-producing countries, thus showing data biases when used at any new location thus it gives rise to a need of creating a dataset from scratch to verify the results of research. Grape is available in different sizes, colors, seed sizes, and shapes which makes its detection, through simple Computer vision, even more challenging. This research addresses this issue by bringing the solution to this problem by using CNN and Neural Networks using the newly created dataset from local farms as the other research and the methods used don't address issues faced locally by the farmers. YOLO has been selected to be trained on the locally collected dataset of grapes.","PeriodicalId":447565,"journal":{"name":"2023 International Conference on Robotics and Automation in Industry (ICRAI)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115459552","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Natural Disaster Damage Assessment using Semantic Segmentation of UAV Imagery 基于无人机图像语义分割的自然灾害损害评估

2023 International Conference on Robotics and Automation in Industry (ICRAI) Pub Date : 2023-03-03 DOI: 10.1109/ICRAI57502.2023.10089539

Muhammad Haroon Asad, Malik Muhammad Asim, Muhammad Naeem Mumtaz Awan, M. Yousaf

{"title":"Natural Disaster Damage Assessment using Semantic Segmentation of UAV Imagery","authors":"Muhammad Haroon Asad, Malik Muhammad Asim, Muhammad Naeem Mumtaz Awan, M. Yousaf","doi":"10.1109/ICRAI57502.2023.10089539","DOIUrl":"https://doi.org/10.1109/ICRAI57502.2023.10089539","url":null,"abstract":"Numerous natural disasters due to climate change pose major threats to the sustainability of public infrastructure and human lives. For emergency rescue and recovery during a disaster, a rapid and accurate evaluation of disaster damage is essential. In recent years, the Transformer has gained popularity in a number of tasks related to computer vision, which offers tremendous potential for improving the accuracy of disaster damage assessments. Our research aims to determine whether Vision Transformer (ViT) can be used to assess natural disaster damage on high-resolution Unmanned Aerial Vehicle (UAV) data in comparison with conventional deep-learning semantic segmentation techniques. We discuss if Transformer can perform better than CNNs in accurately assessing the damage caused in order to bridge the gap. Detailed performance comparison of state-of-art deep learning semantic segmentation models (UNET, Segnet, PSPNet, Deeplabv3+) and Transformer framework (SegFormer) for damage assessment is presented. The experimentation is performed on both natural disaster damage datasets (RescueNet, FloodNet). The study supported SegFormer as the most appropriate model for estimating disaster damage, with mIoUs of 96% on the RescueNet dataset and 82.22% on the FloodNet dataset, respectively. The Transformer is capable of outperforming conventional segmentation CNNs in understanding the entirety of the scene and assessing the severity of the damage, based on both quantitative evaluation and visual results.","PeriodicalId":447565,"journal":{"name":"2023 International Conference on Robotics and Automation in Industry (ICRAI)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116716252","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1