International Journal of Intelligent Robotics and Applications最新文献

{"title":"ROS-based multi-sensor integrated localization system for cost-effective and accurate indoor navigation system","authors":"Achmad Syahrul Irwansyah, Budi Heryadi, Dyah Kusuma Dewi, Roni Permana Saputra, Zainal Abidin","doi":"10.1007/s41315-024-00350-1","DOIUrl":"https://doi.org/10.1007/s41315-024-00350-1","url":null,"abstract":"<p>Accurate localization is essential for enabling intelligent autonomous navigation in indoor environments. While global navigation satellite systems (GNSS) provide efficient outdoor solutions, applications in indoor environments require alternative approaches to determine the vehicle's global position. This study investigates a ROS-based multi-sensor integrated localization system utilizing wheel odometry, inertial measurement unit (IMU), and 2D light detection and ranging (LiDAR) based simultaneous localization and mapping (SLAM) for cost-effective and accurate indoor autonomous vehicle (AV) navigation. The paper analyzes the limitations of wheel odometry and IMU, highlighting their susceptibility to errors. To address these limitations, the proposed system leverages LiDAR SLAM for real-time map generation and pose correction. The Karto SLAM package from robot operating system (ROS) is chosen due to its superior performance according to the literature. Results indicate that the integration of these technologies reduces localization errors significantly, with the system achieving a high degree of accuracy in pose estimation under various test conditions. The experimental validation shows that the proposed system maintains consistent performance, proving its potential for widespread application in environments where GNSS is unavailable.</p>","PeriodicalId":44563,"journal":{"name":"International Journal of Intelligent Robotics and Applications","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141258995","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}

{"title":"Automated classification of electrical network high-voltage tower insulator cleanliness using deep neural networks","authors":"Hericles Ferraz, Rogério Sales Gonçalves, Breno Batista Moura, Daniel Edgardo Tió Sudbrack, Paulo Victor Trautmann, Bruno Clasen, Rafael Zimmermann Homma, Reinaldo A. C. Bianchi","doi":"10.1007/s41315-024-00349-8","DOIUrl":"https://doi.org/10.1007/s41315-024-00349-8","url":null,"abstract":"<p>String insulators are components in high-voltage towers responsible for preventing energy dissipation through the tower structure; that is, they are responsible for isolating the high voltage in the electrical network cables. These string insulators must be clean for best performance and to avoid malfunctions. Verifying the necessity for cleaning/washing is most often performed by human visual observation, which can lead to interpretation errors, in addition to bringing risks to the physical integrity of humans in the vicinity of these electrical systems. Thus, this paper aims to develop an algorithm to detect and classify these insulators. The proposed algorithm uses artificial intelligence techniques and analyzes the image, inferring the state of cleanliness of the analyzed insulator. For the development of this algorithm, it was necessary to build a synthetic database using CAD software such as Inventor and Unity-3D due to image limitations available from dirty insulator strings. In this paper, two distinct neural networks are built using supervised learning techniques, where the first one is for detecting the chain of insulators, and the second is for detecting the type of dirt on the disk surface. In the first stage, techniques that use supervised learning are studied, more aimed explicitly at semantic segmentation networks, and in the second stage, classification deep neural networks were used to detect the type of impurities. In detecting insulator strings, an average dice coefficient of 0.95 was achieved for simulated images and 0.92 for natural images, with learning parameters based on a database with only simulated images. The average accuracy obtained in the dirt classification stage was 0.98.</p>","PeriodicalId":44563,"journal":{"name":"International Journal of Intelligent Robotics and Applications","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141258973","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}

{"title":"Nonlinear modelling and dynamics of spatial multi-link rigid-flexible manipulator with moving platform","authors":"Pravesh Kumar, Barun Pratiher","doi":"10.1007/s41315-024-00344-z","DOIUrl":"https://doi.org/10.1007/s41315-024-00344-z","url":null,"abstract":"<p>The demand for developing lighter manipulators, particularly in various long-reach applications, has surged significantly. In many of these applications, inherent structural flexibilities are unavoidable and lead to vibrations. Consequently, these residual vibrations detrimentally affect working efficiency and positioning accuracy. The present work introduces a novel approach by formulating a nonlinear dynamical model of a spatial multi-link manipulator mounted on a mobile platform. This model incorporates both rigid and flexible links, as well as the payload, enabling a comprehensive study of end-point residual vibration characteristics. The dynamic modeling employed in this study accounts for the interplay of coupled geometric and inertial nonlinearities arising from motion interactions among joints, actuators, and elastic link deflections. The manipulator configuration comprises rigid components and two 3D-flexible links actuated by prismatic and revolute joints, respectively. The flexible links are modelled using Euler–Bernoulli beam elements, while time-dependent in-plane motion is imparted to the rigid link. Utilizing Hamilton’s variational principle, a set of nonlinear governing equations of motion is analytically derived. Subsequently, an independent generalized coordinates system is adopted to transform the equations of motion into a nonlinear reduced form. This is achieved through discretization of the spatio-temporal equations, facilitating the analysis of trajectory dynamics for the robotic manipulator. The residual vibration characteristics at the payload end were explored graphically by applying generalized sinusoidal and bang-bang torque profiles to their respective joints. Nonlinear structural flexibility and material properties emerge as pivotal factors influencing these residual end-point vibrations. It has been observed that the bang-bang torque profile extends the settling period in residual vibration due to its intricate transition characteristics, in contrast to the sinusoidal motion profile with a specific torque duty cycle. Numerical simulations highlight that variations in physical and geometric variables significantly impact end-point residual vibrations and joint deflections, potentially leading to positioning errors in the control of spatial flexible manipulators.</p>","PeriodicalId":44563,"journal":{"name":"International Journal of Intelligent Robotics and Applications","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141197583","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}

{"title":"Focused section on new trends on intelligent automation by industrial robots","authors":"Silu Chen, Bo Tao, Fei Chen, Xiaocong Li, Chenguang Yang, Rui Yang","doi":"10.1007/s41315-024-00348-9","DOIUrl":"https://doi.org/10.1007/s41315-024-00348-9","url":null,"abstract":"<p>Industrial robots have been widely used in manufacturing automobiles and consumable electronics, logistics, biomedical engineering, and many other industrial sectors. However, the need to enhance their adaptability, accuracy, and autonomy remains high, enabling them to be competent in advanced application scenarios, such as human–robot collaboration, flexible manufacturing, precision engineering, and large-scale automation. This focused section competitively selects the 10 research papers to disseminate new design, planning, and control methodologies of industrial robots toward intelligent automation.</p>","PeriodicalId":44563,"journal":{"name":"International Journal of Intelligent Robotics and Applications","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141197931","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}

{"title":"Systematic literature review of Fused Deposition Modeling (FDM) strain sensor and soft pneumatic actuator","authors":"H. Mastrisiswadi, Wangi Pandan Sari, Herianto, A. Tontowi","doi":"10.1007/s41315-024-00346-x","DOIUrl":"https://doi.org/10.1007/s41315-024-00346-x","url":null,"abstract":"","PeriodicalId":44563,"journal":{"name":"International Journal of Intelligent Robotics and Applications","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141101371","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}

{"title":"Optimization of complex surface milling parameters based on HSS-MFM and OBL-NSGA-II","authors":"Yang Yang, Yang Liu, Yuanyuan Wang, Dong-yang Zhen, Chen Su, Jiang Wang, Yi-da Liu","doi":"10.1007/s41315-024-00338-x","DOIUrl":"https://doi.org/10.1007/s41315-024-00338-x","url":null,"abstract":"","PeriodicalId":44563,"journal":{"name":"International Journal of Intelligent Robotics and Applications","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141107197","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}

{"title":"Improving robot-to-human communication using flexible display technology as a robotic-skin-interface: a co-design study","authors":"Constantin Scholz, Hoang-Long Cao, Ilias El Makrini, Susanne Niehaus, Maximilian Kaufmann, D. Cheyns, Nima Roshandel, Aleksander Burkiewicz, Mariane Shhaitly, Emil Imrith, Jan Genoe, Xavier Rottenberg, Peter Gerets, B. Vanderborght","doi":"10.1007/s41315-024-00343-0","DOIUrl":"https://doi.org/10.1007/s41315-024-00343-0","url":null,"abstract":"","PeriodicalId":44563,"journal":{"name":"International Journal of Intelligent Robotics and Applications","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141109338","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}

{"title":"A survey on pest detection and classification in field crops using artificial intelligence techniques","authors":"P. Venkatasaichandrakanth, M. Iyapparaja","doi":"10.1007/s41315-024-00347-w","DOIUrl":"https://doi.org/10.1007/s41315-024-00347-w","url":null,"abstract":"","PeriodicalId":44563,"journal":{"name":"International Journal of Intelligent Robotics and Applications","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141118674","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}

{"title":"Research on compliant human–robot interaction based on admittance control strategy for shoulder rehabilitation exoskeleton with CGH self-alignment function","authors":"Huimin Shen, Xuanmin Liu, Kangming Liu, Yao Yao, Xin Weng, Lihong Yang","doi":"10.1007/s41315-024-00345-y","DOIUrl":"https://doi.org/10.1007/s41315-024-00345-y","url":null,"abstract":"","PeriodicalId":44563,"journal":{"name":"International Journal of Intelligent Robotics and Applications","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141118499","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}

{"title":"Design and development of universal soft robotic end effector through machine learning on the IRB 360 robot","authors":"Prabhu Sethuramalingam, M. Uma, V. Darshan, K. S. Sumesh","doi":"10.1007/s41315-024-00339-w","DOIUrl":"https://doi.org/10.1007/s41315-024-00339-w","url":null,"abstract":"<p>The end effector (gripper) is an important part of a robotic system that is used for industrial and domestic tasks like grasping, carrying, manipulating, assembling, painting, and so on. For handling different types of objects hard as well as soft, require different types of the gripper. The employment of compliant soft-robotic grasping systems, which are characterized by high flexibility in terms of workpiece shape, dimension, and anatomy, is a good method to incorporate greater flexibility into production. The study's major goal is to build and analyses the soft-robotic grippers in terms of repeatability with large payload capacities. End effector (soft gripper) control is crucial for precision work by applying different gripping forces according to the object going to pick. The selection of suitable gripping force for a particular object is done by the process of machine learning (ML). The soft gripper is designed, fabricated, and tested using Industrial Robot (IRB 360) flex picker robot. The virtual environment is created to move the linear path using Robot studio software with rapid programming language. The accuracy, precision, recall, and receiver operating characteristic curve (ROC) curve are analyzed and predict the gripper force accurately with 94% when compared with experimental value. The gripper is working effectively from 1.4 to 2.8 bars with a maximum payload of 500 g. The soft flexible gripper angle is measured based on the pressure using an image processing edge detection technique. The optimized best possible gripping force is predicted using different objects and control action is done to supply exact force to the gripper.</p>","PeriodicalId":44563,"journal":{"name":"International Journal of Intelligent Robotics and Applications","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140930932","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}