Zuha Anjum, S. Samo, A. Nighat, Akhtar Un Nisa, Muhammad Ali Soomro, Reza Alayi
In disaster areas, robot manipulators are used to rescue and clearance of sites. Because of the damaged area, they encounter disturbances like obstacles, and limited workspace to explore the area and to achieve the location of the victims. Increasing the degrees of freedom is required to boost the adaptability of manipulators to avoid disturbances, and to obtain the fast desired position and precise movements of the end-effector. These robot manipulators offer a reliable way to handle the barrier challenges since they can search in places that humans can't reach. In this research paper, the 9-DOF robotic manipulator is designed, and an analytical model is developed to examine the system’s behavior in different scenarios. The kinematic and dynamic representation of the proposed model is analyzed to obtain the translation or rotation, and joint torques to achieve the expected position, velocity, and acceleration respectively. The number of degrees may be raised to avoid disturbances, and to obtain the fast desired position and precise movements of the end-effector. The simulation of developed models is performed to ensure the adaptable movement of the manipulators working in distinct configurations and controlling their motion thoroughly and effectively. In the proposed configuration the joints can easily be moved to achieve the desired position of the end-effector and the results are satisfactory. The simulation results show that the redundant manipulator achieves the victim location with various configurations of the manipulator. Results reveal the effectiveness and efficacy of the proposed system.
{"title":"Design and Modeling of 9 Degrees of Freedom Redundant Robotic Manipulator","authors":"Zuha Anjum, S. Samo, A. Nighat, Akhtar Un Nisa, Muhammad Ali Soomro, Reza Alayi","doi":"10.18196/jrc.v3i6.15958","DOIUrl":"https://doi.org/10.18196/jrc.v3i6.15958","url":null,"abstract":"In disaster areas, robot manipulators are used to rescue and clearance of sites. Because of the damaged area, they encounter disturbances like obstacles, and limited workspace to explore the area and to achieve the location of the victims. Increasing the degrees of freedom is required to boost the adaptability of manipulators to avoid disturbances, and to obtain the fast desired position and precise movements of the end-effector. These robot manipulators offer a reliable way to handle the barrier challenges since they can search in places that humans can't reach. In this research paper, the 9-DOF robotic manipulator is designed, and an analytical model is developed to examine the system’s behavior in different scenarios. The kinematic and dynamic representation of the proposed model is analyzed to obtain the translation or rotation, and joint torques to achieve the expected position, velocity, and acceleration respectively. The number of degrees may be raised to avoid disturbances, and to obtain the fast desired position and precise movements of the end-effector. The simulation of developed models is performed to ensure the adaptable movement of the manipulators working in distinct configurations and controlling their motion thoroughly and effectively. In the proposed configuration the joints can easily be moved to achieve the desired position of the end-effector and the results are satisfactory. The simulation results show that the redundant manipulator achieves the victim location with various configurations of the manipulator. Results reveal the effectiveness and efficacy of the proposed system.","PeriodicalId":443428,"journal":{"name":"Journal of Robotics and Control (JRC)","volume":"124 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128141486","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}
The article deals with the management of a fleet of AMR robots that perform logistics in production. The entire system design is implemented in the ROS environment - state of the art for the development in robotics. Four already available solutions for fleet management in ROSe are analyzed in detail in the article. These solutions fail when there is a need to change the route plan in a dynamically changing environment. Likewise, some did not sufficiently synchronize the movement of the robots and collisions occurred or, with a larger number of robots, represented an enormous computational load. Our solution was designed to be as simple and reliable as possible for industrial use. It is based on a combination of semi-autonomous and centralized approach. A hybrid map is used for planning the movement of the robot fleet, which provides the advantages of both a metric and a topological map. This route map for a fleet of robots can be easily drawn in readily available CAD software. Synchronization of robots was designed on the principle of semaphore or mutex, which enabled the use of bidirectional paths. The results are verified in simulations and were aimed at verifying the proposed robot synchronization. It was confirmed that the proposed synchronization slows down the robots, but there were no collision situations. By separating route planning from synchronization, we simplified the entire fleet management process and thus created a very efficient system for network and hardware resources. In addition, the system is easily expandable.
{"title":"Fleet Management System for an Industry Environment","authors":"Jakub Hažík, Martin Dekan, Peter Beno, F. Duchoň","doi":"10.18196/jrc.v3i6.16298","DOIUrl":"https://doi.org/10.18196/jrc.v3i6.16298","url":null,"abstract":"The article deals with the management of a fleet of AMR robots that perform logistics in production. The entire system design is implemented in the ROS environment - state of the art for the development in robotics. Four already available solutions for fleet management in ROSe are analyzed in detail in the article. These solutions fail when there is a need to change the route plan in a dynamically changing environment. Likewise, some did not sufficiently synchronize the movement of the robots and collisions occurred or, with a larger number of robots, represented an enormous computational load. Our solution was designed to be as simple and reliable as possible for industrial use. It is based on a combination of semi-autonomous and centralized approach. A hybrid map is used for planning the movement of the robot fleet, which provides the advantages of both a metric and a topological map. This route map for a fleet of robots can be easily drawn in readily available CAD software. Synchronization of robots was designed on the principle of semaphore or mutex, which enabled the use of bidirectional paths. The results are verified in simulations and were aimed at verifying the proposed robot synchronization. It was confirmed that the proposed synchronization slows down the robots, but there were no collision situations. By separating route planning from synchronization, we simplified the entire fleet management process and thus created a very efficient system for network and hardware resources. In addition, the system is easily expandable.","PeriodicalId":443428,"journal":{"name":"Journal of Robotics and Control (JRC)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121594136","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}
Electrical machines based on permanent magnet material excitations have been applied in many sectors since they are distinguished by their high torque-to-size ratio and offer high efficiency. Brushless permanent magnetic direct current (BLPMDC) motors are one type of these machines. They are preferable over conventional DC motors. one of the main challengings of the BLPMDC motor drives is the inherited feature of nonlinearity. Therefore, a conventional PID controller would not be an efficient choice for the speed control of such motors. The object of this paper is to design an efficient speed control for the BLPMDC motor. The proposed controller is based on the Fuzzy logic technique. MATLAB/ Simulink has been employed to design and test the drive system. Simulations were carried out for three cases, the first without a controller, the other using conventional control, and the third using expert systems. The results proved the possibility of improving the engine's working performance using the control systems. They also proved that the adoption of expert systems is better than the traditional nonlinear systems. The simulation response shows that the Rise Time(tr) at PID equals 66.306ms, while it equals 19.530ms for the Fuzzy logic controller. Moreover, Overshoot for PID and Fuzzy logic controller are 6.989% and 1.531%, respectively. On the other hand, undershoot is equal to 1.788% and 11.924% for PID and Fuzzy logic controller, respectively.
{"title":"Fuzzy Logic Control and PID Controller for Brushless Permanent Magnetic Direct Current Motor: A Comparative Study","authors":"A. Shuraiji, S. W. Shneen","doi":"10.18196/jrc.v3i6.15974","DOIUrl":"https://doi.org/10.18196/jrc.v3i6.15974","url":null,"abstract":"Electrical machines based on permanent magnet material excitations have been applied in many sectors since they are distinguished by their high torque-to-size ratio and offer high efficiency. Brushless permanent magnetic direct current (BLPMDC) motors are one type of these machines. They are preferable over conventional DC motors. one of the main challengings of the BLPMDC motor drives is the inherited feature of nonlinearity. Therefore, a conventional PID controller would not be an efficient choice for the speed control of such motors. The object of this paper is to design an efficient speed control for the BLPMDC motor. The proposed controller is based on the Fuzzy logic technique. MATLAB/ Simulink has been employed to design and test the drive system. Simulations were carried out for three cases, the first without a controller, the other using conventional control, and the third using expert systems. The results proved the possibility of improving the engine's working performance using the control systems. They also proved that the adoption of expert systems is better than the traditional nonlinear systems. The simulation response shows that the Rise Time(tr) at PID equals 66.306ms, while it equals 19.530ms for the Fuzzy logic controller. Moreover, Overshoot for PID and Fuzzy logic controller are 6.989% and 1.531%, respectively. On the other hand, undershoot is equal to 1.788% and 11.924% for PID and Fuzzy logic controller, respectively.","PeriodicalId":443428,"journal":{"name":"Journal of Robotics and Control (JRC)","volume":"725 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122998452","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}
This study was based on the dynamic modeling and parameter characterization of the one-link robot arm driven by pneumatic artificial muscles. This work discusses an up-to-date control design based on the notion of a conventional and optimal backstepping controller for regulating a one-link robot arm with conflicting biceps and triceps positions supplied by pneumatic artificial muscles. The main problems found in systems that utilize pneumatic artificial muscle as actuators are primarily the large uncertainties, non-linearities, and time-varying features that severely impede movement performance in tracking control. In consideration of the uncertainty, high nonlinearity, and external disturbances that can exist during the motion. Lyapunov-based backstepping control technique was utilized to assure the stability of the system with improved dynamic performance. The bat algorithm optimization method is utilized in order to modify the variables used in the design of the controller to enhance the efficiency of the suggested controller. According to the conclusions, a quantitative comparison of the response in the PAM actuated the arm model in the current study and earlier investigations with the Backstepping controlled system revealed fair agreement with a variation of 37.5% from the optimal classical synergetic controller. In addition, computer simulations were utilized in order to compare the effectiveness of the proposed conventional controls and the optimal background. It has been proven that an optimal controller can control the uncertainties and maintain the controlled system’s stability.
{"title":"A Comparative Study Between Convolution and Optimal Backstepping Controller for Single Arm Pneumatic Artificial Muscles","authors":"A. S. Ahmed, S. Kadhim","doi":"10.18196/jrc.v3i6.16064","DOIUrl":"https://doi.org/10.18196/jrc.v3i6.16064","url":null,"abstract":"This study was based on the dynamic modeling and parameter characterization of the one-link robot arm driven by pneumatic artificial muscles. This work discusses an up-to-date control design based on the notion of a conventional and optimal backstepping controller for regulating a one-link robot arm with conflicting biceps and triceps positions supplied by pneumatic artificial muscles. The main problems found in systems that utilize pneumatic artificial muscle as actuators are primarily the large uncertainties, non-linearities, and time-varying features that severely impede movement performance in tracking control. In consideration of the uncertainty, high nonlinearity, and external disturbances that can exist during the motion. Lyapunov-based backstepping control technique was utilized to assure the stability of the system with improved dynamic performance. The bat algorithm optimization method is utilized in order to modify the variables used in the design of the controller to enhance the efficiency of the suggested controller. According to the conclusions, a quantitative comparison of the response in the PAM actuated the arm model in the current study and earlier investigations with the Backstepping controlled system revealed fair agreement with a variation of 37.5% from the optimal classical synergetic controller. In addition, computer simulations were utilized in order to compare the effectiveness of the proposed conventional controls and the optimal background. It has been proven that an optimal controller can control the uncertainties and maintain the controlled system’s stability.","PeriodicalId":443428,"journal":{"name":"Journal of Robotics and Control (JRC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128999066","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}
In recent years, artificial intelligence has proved its potential in many fields, especially in computer vision. Facial recognition is one of the most essential tasks in the field of computer vision with various prospective applications from academic research to intelligence service. In this paper, we propose an efficient deep learning approach to facial recognition. Our approach utilizes the architecture of ArcFace model based on the backbone MobileNet V2, in deep convolutional neural network (DCNN). Assistive techniques to increase highly distinguishing features in facial recognition. With the supports of the facial authentication combines with hand gestures recognition, users will be able to monitor and control his home through his mobile phone/tablet/PC. Moreover, they communicate with data and connect to smart devices easily through IoT technology. The overall proposed model is 97% of accuracy and a processing speed of 25 FPS. The interface of the smart home demonstrates the successful functions of real-time operations.
{"title":"Smart home Management System with Face Recognition Based on ArcFace Model in Deep Convolutional Neural Network","authors":"T. Dang","doi":"10.18196/jrc.v3i6.15978","DOIUrl":"https://doi.org/10.18196/jrc.v3i6.15978","url":null,"abstract":"In recent years, artificial intelligence has proved its potential in many fields, especially in computer vision. Facial recognition is one of the most essential tasks in the field of computer vision with various prospective applications from academic research to intelligence service. In this paper, we propose an efficient deep learning approach to facial recognition. Our approach utilizes the architecture of ArcFace model based on the backbone MobileNet V2, in deep convolutional neural network (DCNN). Assistive techniques to increase highly distinguishing features in facial recognition. With the supports of the facial authentication combines with hand gestures recognition, users will be able to monitor and control his home through his mobile phone/tablet/PC. Moreover, they communicate with data and connect to smart devices easily through IoT technology. The overall proposed model is 97% of accuracy and a processing speed of 25 FPS. The interface of the smart home demonstrates the successful functions of real-time operations.","PeriodicalId":443428,"journal":{"name":"Journal of Robotics and Control (JRC)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123447881","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}
Linear Parameter Varying models-based Model Predictive Control (LPV-MPC) has stood out in manipulator robots because it presents well-rejection to dynamic uncertainties in flexible joints. However, it has become too weak when the MPC's optimization problem does not include kinematic constraints-based conditions. This paper uses dynamic confined space of velocities (DCSV) to include these conditions as a recursive polytopic constraint, guaranteeing optimal dependency on a simplex scheduling parameter. To this end, the local frame's velocities and torque/force preload of joints (related to violation of kinematic constraints) are associated with different time scale dynamics such that DCSV correlates them as a polytope. So, a classical LPV-MPC will be updated using a dynamic programming approach according to the DCSV-based polytope. As a result, one lemma about DCSV-based recursive polytope and a five-step procedure for two decoupled close-loop schemes with different time scales compose the LPV-MPC proposed method. Numerical validation shows that even for relevant flexibility situations, trajectory tracking performance is improved by tuning finite horizons and optimization problem constraints regarding DCSV's behavior.
{"title":"Control of Flexible Manipulator Robots Based on Dynamic Confined Space of Velocities: Dynamic Programming Approach","authors":"C. P. Peña Fernández","doi":"10.18196/jrc.v3i6.16454","DOIUrl":"https://doi.org/10.18196/jrc.v3i6.16454","url":null,"abstract":"Linear Parameter Varying models-based Model Predictive Control (LPV-MPC) has stood out in manipulator robots because it presents well-rejection to dynamic uncertainties in flexible joints. However, it has become too weak when the MPC's optimization problem does not include kinematic constraints-based conditions. This paper uses dynamic confined space of velocities (DCSV) to include these conditions as a recursive polytopic constraint, guaranteeing optimal dependency on a simplex scheduling parameter. To this end, the local frame's velocities and torque/force preload of joints (related to violation of kinematic constraints) are associated with different time scale dynamics such that DCSV correlates them as a polytope. So, a classical LPV-MPC will be updated using a dynamic programming approach according to the DCSV-based polytope. As a result, one lemma about DCSV-based recursive polytope and a five-step procedure for two decoupled close-loop schemes with different time scales compose the LPV-MPC proposed method. Numerical validation shows that even for relevant flexibility situations, trajectory tracking performance is improved by tuning finite horizons and optimization problem constraints regarding DCSV's behavior.","PeriodicalId":443428,"journal":{"name":"Journal of Robotics and Control (JRC)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125830955","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}
Muhammad Maaruf, Aminu Babangida, H. Almusawi, Peter Szemes Tamas
Over the years, researchers have addressed several control problems of various classes of nonlinear systems. This article considers a class of uncertain strict feedback nonlinear system with unknown external disturbances and asymmetric input dead-zone. Designing a tracking controller for such system is very complex and challenging. This article aims to design a finite-time adaptive neural network backstepping tracking control for the nonlinear system under consideration. In addition, all unknown disturbances and nonlinear functions are lumped together and approximated by radial basis function neural network (RBFNN). Moreover, no prior information about the boundedness of the dead-zone parameters is required in the controller design. With the aid of a Lyapunov candidate function, it has been shown that the tracking errors converge near the origin in finite-time. Simulation results testify that the proposed control approach can force the output to follow the reference trajectory in a short time despite the presence of asymmetric input dead-zone and external disturbances. At last, in order to highlight the effectiveness of the proposed control method, it is applied to a quadrotor unmanned aerial vehicle (UAV).
{"title":"Neural Network-based Finite-time Control of Nonlinear Systems with Unknown Dead-zones: Application to Quadrotors","authors":"Muhammad Maaruf, Aminu Babangida, H. Almusawi, Peter Szemes Tamas","doi":"10.18196/jrc.v3i6.15355","DOIUrl":"https://doi.org/10.18196/jrc.v3i6.15355","url":null,"abstract":"Over the years, researchers have addressed several control problems of various classes of nonlinear systems. This article considers a class of uncertain strict feedback nonlinear system with unknown external disturbances and asymmetric input dead-zone. Designing a tracking controller for such system is very complex and challenging. This article aims to design a finite-time adaptive neural network backstepping tracking control for the nonlinear system under consideration. In addition, all unknown disturbances and nonlinear functions are lumped together and approximated by radial basis function neural network (RBFNN). Moreover, no prior information about the boundedness of the dead-zone parameters is required in the controller design. With the aid of a Lyapunov candidate function, it has been shown that the tracking errors converge near the origin in finite-time. Simulation results testify that the proposed control approach can force the output to follow the reference trajectory in a short time despite the presence of asymmetric input dead-zone and external disturbances. At last, in order to highlight the effectiveness of the proposed control method, it is applied to a quadrotor unmanned aerial vehicle (UAV).","PeriodicalId":443428,"journal":{"name":"Journal of Robotics and Control (JRC)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128844353","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}
This paper presents a new combination between the Model Reference Adaptive Control (MRAC) with several types of PID’s controllers (PID, Fractional order PID (FOPID), and Nonlinear PID (NPID)) optimized using a new Covid-19 algorithm. The proposed control techniques had been applied on a new model for an electric-wind vehicle, which can catch the wind that blows in the opposite direction of a moving vehicle to receive wind; a wind turbine is installed on the vehicle’s front. The generator converts wind energy into electricity and stores it into a backup battery to switch it when the primary battery is empty. The simulation results prove that the new model of electric–wind vehicles will save power and allow the vehicle to continue moving while the other battery charges. In addition, a comparative study between different types of control algorithms had been developed and investigated to improve the vehicle dynamic response. The comparison shows that the MRAC with the NPID compensator can absorb the nonlinearity (air resistance and wheel friction) where it has a minimum overshoot, rise time, and settling time (35 seconds) among other control techniques compensators (PID and FOPID).
{"title":"Adaptive Controller with PID, FOPID, and NPID Compensators for Tracking Control of Electric – Wind Vehicle","authors":"Mohamed A. Shamseldin","doi":"10.18196/jrc.v3i5.15855","DOIUrl":"https://doi.org/10.18196/jrc.v3i5.15855","url":null,"abstract":"This paper presents a new combination between the Model Reference Adaptive Control (MRAC) with several types of PID’s controllers (PID, Fractional order PID (FOPID), and Nonlinear PID (NPID)) optimized using a new Covid-19 algorithm. The proposed control techniques had been applied on a new model for an electric-wind vehicle, which can catch the wind that blows in the opposite direction of a moving vehicle to receive wind; a wind turbine is installed on the vehicle’s front. The generator converts wind energy into electricity and stores it into a backup battery to switch it when the primary battery is empty. The simulation results prove that the new model of electric–wind vehicles will save power and allow the vehicle to continue moving while the other battery charges. In addition, a comparative study between different types of control algorithms had been developed and investigated to improve the vehicle dynamic response. The comparison shows that the MRAC with the NPID compensator can absorb the nonlinearity (air resistance and wheel friction) where it has a minimum overshoot, rise time, and settling time (35 seconds) among other control techniques compensators (PID and FOPID). ","PeriodicalId":443428,"journal":{"name":"Journal of Robotics and Control (JRC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125861503","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}
Robotics forms an integral part of industry 4.0, the industrial revolution of the 21st century. This paper presents a bibliometric analysis of Web of Science (WoS) indexed publications addressing this emerging field from 2011 till June 2022. WoS research publications were firstly analysed along multiple verticals such as annual counts, types, publishing sources, research directions, researchers, organizations, and countries. Next, co-authorship collaborations among authors, organizations, and countries were discovered. This was followed by an analysis of co-occurring keywords related to robotics in industry 4.0. Finally, a detailed citation analysis was carried out to unearth citation linkages among authors, institutions, documents, nations, and journals. Latest trends, under-investigated topics, and future directions are also discussed. Primary results indicate that more than 3000 articles are being published annually in this emerging field, with a total of 18,893 documents published in WoS during the last decade. The 'IEEE Access', Chinese Academy of Science, Wang Y. (USA), and the USA emerged as the topmost productive journal, institution, author, and nation. Porpiglia Francesco (Italy), Chinese Academy Science and USA obtained the highest co-authorship total link strength (TLS); whereas Lee Chengkuo (Singapore), China, Chinese Academy Science, and the IEEE Access scored the highest citation TLS among authors, countries, organizations, and sources respectively. Machine learning (ML) emerged as the highest co-occurring keyword, followed by artificial intelligence (AI). Computer Science emerged as the most trending research domain, followed by general applications. In the future, ML and AI will advance more sophisticated robots in industry 4.0 systems.
机器人技术是21世纪工业革命工业4.0的重要组成部分。本文对2011年至2022年6月科学网(Web of Science, WoS)索引的这一新兴领域的出版物进行了文献计量分析。首先从年度数量、类型、出版来源、研究方向、研究人员、组织和国家等多个垂直维度对WoS研究出版物进行分析。接下来，作者、组织和国家之间的合作被发现。随后分析了工业4.0中与机器人相关的共同出现的关键词。最后，进行了详细的引文分析，揭示了作者、机构、文献、国家和期刊之间的引文联系。还讨论了最新的趋势，未调查的主题和未来的方向。初步结果表明，每年在这个新兴领域发表3000多篇文章，在过去十年中，世界卫生组织共发表了18 893份文件。“IEEE Access”、中国科学院、王毅(美国)和美国成为产出最高的期刊、机构、作者和国家。意大利的Porpiglia Francesco、中国科学院和美国的共同作者总链接强度(TLS)最高;而李成国(新加坡)、中国、中国科学院和IEEE Access分别在作者、国家、组织和来源中获得了最高的引用TLS。同时出现最多的关键词是机器学习(ML)，其次是人工智能(AI)。计算机科学成为最热门的研究领域，其次是通用应用。未来，机器学习和人工智能将在工业4.0系统中推进更复杂的机器人。
{"title":"Robotics in Industry 4.0: A Bibliometric Analysis (2011-2022)","authors":"R. Aravind Sekhar, Pritesh Shah, I. Iswanto","doi":"10.18196/jrc.v3i5.15453","DOIUrl":"https://doi.org/10.18196/jrc.v3i5.15453","url":null,"abstract":"Robotics forms an integral part of industry 4.0, the industrial revolution of the 21st century. This paper presents a bibliometric analysis of Web of Science (WoS) indexed publications addressing this emerging field from 2011 till June 2022. WoS research publications were firstly analysed along multiple verticals such as annual counts, types, publishing sources, research directions, researchers, organizations, and countries. Next, co-authorship collaborations among authors, organizations, and countries were discovered. This was followed by an analysis of co-occurring keywords related to robotics in industry 4.0. Finally, a detailed citation analysis was carried out to unearth citation linkages among authors, institutions, documents, nations, and journals. Latest trends, under-investigated topics, and future directions are also discussed. Primary results indicate that more than 3000 articles are being published annually in this emerging field, with a total of 18,893 documents published in WoS during the last decade. The 'IEEE Access', Chinese Academy of Science, Wang Y. (USA), and the USA emerged as the topmost productive journal, institution, author, and nation. Porpiglia Francesco (Italy), Chinese Academy Science and USA obtained the highest co-authorship total link strength (TLS); whereas Lee Chengkuo (Singapore), China, Chinese Academy Science, and the IEEE Access scored the highest citation TLS among authors, countries, organizations, and sources respectively. Machine learning (ML) emerged as the highest co-occurring keyword, followed by artificial intelligence (AI). Computer Science emerged as the most trending research domain, followed by general applications. In the future, ML and AI will advance more sophisticated robots in industry 4.0 systems.","PeriodicalId":443428,"journal":{"name":"Journal of Robotics and Control (JRC)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115835910","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}
N. S. Abu, W. Bukhari, M. Adli, S. Omar, S. A. Sohaimeh
Mobile robots are increasingly being applied in a variety of sectors, including agricultural, firefighting, and search and rescue operations. Robotics and autonomous technology research and development have played a major role in making this possible. Before a robot can reliably and effectively navigate a space without human aid, there are still several challenges to be addressed. When planning a path to its destination, the robot should be able to gather information from its surroundings and take the appropriate actions to avoid colliding with obstacles along the way. The following review analyses and compares 200 articles from two databases, Scopus and IEEE Xplore, and selects 60 articles as references from those articles. This evaluation focuses mostly on the accuracy of the different path-planning algorithms. Common collision-free path planning methodologies are examined in this paper, including classical or traditional and modern intelligence techniques, as well as both global and local approaches, in static and dynamic environments. Classical or traditional methods, such as Roadmaps (Visibility Graph and Voronoi Diagram), Potential Fields, and Cell Decomposition, and modern methodologies such as heuristic-based (Dijkstra Method, A* Algorithms, and D* Algorithms), metaheuristics algorithms (such as PSO, Bat Algorithm, ACO, and Genetic Algorithm), and neural systems such as fuzzy neural networks or fuzzy logic (FL) and Artificial Neural Networks (ANN) are described in this report. In this study, we outline the ideas, benefits, and downsides of modeling and path-searching technologies for a mobile robot.
{"title":"A Comprehensive Overview of Classical and Modern Route Planning Algorithms for Self-Driving Mobile Robots","authors":"N. S. Abu, W. Bukhari, M. Adli, S. Omar, S. A. Sohaimeh","doi":"10.18196/jrc.v3i5.14683","DOIUrl":"https://doi.org/10.18196/jrc.v3i5.14683","url":null,"abstract":"Mobile robots are increasingly being applied in a variety of sectors, including agricultural, firefighting, and search and rescue operations. Robotics and autonomous technology research and development have played a major role in making this possible. Before a robot can reliably and effectively navigate a space without human aid, there are still several challenges to be addressed. When planning a path to its destination, the robot should be able to gather information from its surroundings and take the appropriate actions to avoid colliding with obstacles along the way. The following review analyses and compares 200 articles from two databases, Scopus and IEEE Xplore, and selects 60 articles as references from those articles. This evaluation focuses mostly on the accuracy of the different path-planning algorithms. Common collision-free path planning methodologies are examined in this paper, including classical or traditional and modern intelligence techniques, as well as both global and local approaches, in static and dynamic environments. Classical or traditional methods, such as Roadmaps (Visibility Graph and Voronoi Diagram), Potential Fields, and Cell Decomposition, and modern methodologies such as heuristic-based (Dijkstra Method, A* Algorithms, and D* Algorithms), metaheuristics algorithms (such as PSO, Bat Algorithm, ACO, and Genetic Algorithm), and neural systems such as fuzzy neural networks or fuzzy logic (FL) and Artificial Neural Networks (ANN) are described in this report. In this study, we outline the ideas, benefits, and downsides of modeling and path-searching technologies for a mobile robot.","PeriodicalId":443428,"journal":{"name":"Journal of Robotics and Control (JRC)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131780388","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}
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