The development of an autonomous mobile robot (AMR) with an eye-in-hand robot arm atop for depressing elevator button is proposed. The AMR can construct map and perform localization using the ORB-SLAM algorithm (the Oriented FAST (Features from Accelerated Segment Test) and Rotated BRIEF (Binary Robust Independent Elementary Features) feature detector-Simultaneous Localization and Mapping). It is also capable of real-time obstacle avoidance using information from 2D-LiDAR sensors. The AMR, robot manipulator, cameras, and sensors are all integrated under robot operating system (ROS). In experimental investigation to dispatch the AMR for depressing an elevator button, AMR navigation initiating from the laboratory is divided into three parts. First, the AMR initiated navigation using ORB-SLAM for most of the journey to a waypoint nearby the elevator. The resulting mean absolute error (MAE) is 8.5 cm on the x-axis, 10.8 cm on the y-axis, 9.2-degree rotation angle about the z-axis, and the linear displacement from the reference point is 15.1 cm. Next, the ORB-SLAM is replaced by an odometry based 2D-SLAM method for further navigating the AMR from waypoint to a point facing the elevator between 1.5 to 3 meter distance, where the ORB-SLAM is ineffective due to sparse feature points for localization and where the elevator can be clearly detected by an eye-in-hand machine vision onboard the AMR. Finally, the machine vision identifies space position of the elevator and again the odometry based 2D SLAM method is employed for navigating the AMR to front of the elevator between 0.3 to 0.5 meter distance. Only at this stage, the small-size elevator button can be detected and reached by the robot arm on the AMR. An averaged 60% successful rate of button depressing by the AMR starting at the laboratory is obtained in the experiments. Improvements of successful elevator button depressing rate are also pointed out.
{"title":"Hybrid Navigation of an Autonomous Mobile Robot to Depress an Elevator Button","authors":"Pan-Long Wu, Zhe-Ming Zhang, Chuin Jiat Liew, Jinsiang Shaw","doi":"10.14313/jamris/4-2022/30","DOIUrl":"https://doi.org/10.14313/jamris/4-2022/30","url":null,"abstract":"The development of an autonomous mobile robot (AMR) with an eye-in-hand robot arm atop for depressing elevator button is proposed. The AMR can construct map and perform localization using the ORB-SLAM algorithm (the Oriented FAST (Features from Accelerated Segment Test) and Rotated BRIEF (Binary Robust Independent Elementary Features) feature detector-Simultaneous Localization and Mapping). It is also capable of real-time obstacle avoidance using information from 2D-LiDAR sensors. The AMR, robot manipulator, cameras, and sensors are all integrated under robot operating system (ROS). In experimental investigation to dispatch the AMR for depressing an elevator button, AMR navigation initiating from the laboratory is divided into three parts. First, the AMR initiated navigation using ORB-SLAM for most of the journey to a waypoint nearby the elevator. The resulting mean absolute error (MAE) is 8.5 cm on the x-axis, 10.8 cm on the y-axis, 9.2-degree rotation angle about the z-axis, and the linear displacement from the reference point is 15.1 cm. Next, the ORB-SLAM is replaced by an odometry based 2D-SLAM method for further navigating the AMR from waypoint to a point facing the elevator between 1.5 to 3 meter distance, where the ORB-SLAM is ineffective due to sparse feature points for localization and where the elevator can be clearly detected by an eye-in-hand machine vision onboard the AMR. Finally, the machine vision identifies space position of the elevator and again the odometry based 2D SLAM method is employed for navigating the AMR to front of the elevator between 0.3 to 0.5 meter distance. Only at this stage, the small-size elevator button can be detected and reached by the robot arm on the AMR. An averaged 60% successful rate of button depressing by the AMR starting at the laboratory is obtained in the experiments. Improvements of successful elevator button depressing rate are also pointed out.","PeriodicalId":37910,"journal":{"name":"Journal of Automation, Mobile Robotics and Intelligent Systems","volume":"304 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135830055","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}
Pub Date : 2023-10-02DOI: 10.14313/jamris/4-2022/32
Ali Mallem, Fouzi Douak, Beneziza Walid, Bounouara Asma
In this paper a new algorithm of optimization in the field of manipulator robotic control is presented. The proposed control approach based on fast terminal sliding mode control (FTSMC) in order to guarantee the convergence of the position articulations errors to zero in finite time without chattering phenomena, and the firefly algorithm in order to generate the optimal parameters that ensure minimum reaching time and mean square error and achieve better performances, whose ensure the asymptotic stability of the system using a Lyapunov candidate in presence of disturbances. The simulations are applied on a two-link robotic manipulator with different tracking references by using Matlab/ Simulink , results show the efficiency and confirm the robustness of the proposed control strategy.
{"title":"Firefly Algorithm Optimization of Manipulator Robotic Control Based on Fast Terminal Sliding Mode","authors":"Ali Mallem, Fouzi Douak, Beneziza Walid, Bounouara Asma","doi":"10.14313/jamris/4-2022/32","DOIUrl":"https://doi.org/10.14313/jamris/4-2022/32","url":null,"abstract":"In this paper a new algorithm of optimization in the field of manipulator robotic control is presented. The proposed control approach based on fast terminal sliding mode control (FTSMC) in order to guarantee the convergence of the position articulations errors to zero in finite time without chattering phenomena, and the firefly algorithm in order to generate the optimal parameters that ensure minimum reaching time and mean square error and achieve better performances, whose ensure the asymptotic stability of the system using a Lyapunov candidate in presence of disturbances. The simulations are applied on a two-link robotic manipulator with different tracking references by using Matlab/ Simulink , results show the efficiency and confirm the robustness of the proposed control strategy.","PeriodicalId":37910,"journal":{"name":"Journal of Automation, Mobile Robotics and Intelligent Systems","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135831075","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}
Pub Date : 2023-10-02DOI: 10.14313/jamris/4-2022/27
Julia Żaba, Szczepan Paszkiel
The scope of this study refers to the possibility of implementing intelligent artificial limbs for patients after injuries or amputations. Brain-computer technology allows signals to be acquired and sent between the brain and an external device. Upper limb prostheses, however, are quite a complicated tool, because the hand itself has a very complex structure and consists of several joints. The most complicated joint is undoubtedly the saddle joint, which is located at the site of the thumb. You need to demonstrate adequate anatomical knowledge to construct a prosthesis that will be easy to use and resemble a human hand as much as possible. It is also important to create the right control system with the right software that will easily work together with the brain-computer interface. Therefore, the proposed solution in this work is simple. It consists of three parts, which are: the Emotiv EPOC + Neuroheadsets, a control system made of a servo and an Arduino UNO board (with dedicated software), and a hand prosthesis model made in the three-dimensional graphic program Blender and printed using a 3D printing printer. Such a hand prosthesis controlled by a signal from the brain could help people with disabilities after amputations and people who have damaged innervation at the stump site.
{"title":"Concept of Using the Brain-Computer Interface to Control Hand Prosthesis","authors":"Julia Żaba, Szczepan Paszkiel","doi":"10.14313/jamris/4-2022/27","DOIUrl":"https://doi.org/10.14313/jamris/4-2022/27","url":null,"abstract":"The scope of this study refers to the possibility of implementing intelligent artificial limbs for patients after injuries or amputations. Brain-computer technology allows signals to be acquired and sent between the brain and an external device. Upper limb prostheses, however, are quite a complicated tool, because the hand itself has a very complex structure and consists of several joints. The most complicated joint is undoubtedly the saddle joint, which is located at the site of the thumb. You need to demonstrate adequate anatomical knowledge to construct a prosthesis that will be easy to use and resemble a human hand as much as possible. It is also important to create the right control system with the right software that will easily work together with the brain-computer interface. Therefore, the proposed solution in this work is simple. It consists of three parts, which are: the Emotiv EPOC + Neuroheadsets, a control system made of a servo and an Arduino UNO board (with dedicated software), and a hand prosthesis model made in the three-dimensional graphic program Blender and printed using a 3D printing printer. Such a hand prosthesis controlled by a signal from the brain could help people with disabilities after amputations and people who have damaged innervation at the stump site.","PeriodicalId":37910,"journal":{"name":"Journal of Automation, Mobile Robotics and Intelligent Systems","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135831341","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}
Pub Date : 2023-10-02DOI: 10.14313/jamris/4-2022/29
Sergii Filonenko, Anzhelika Stakhova
Abstract The main problem with using acoustic emission to control and diagnostics of composite materials and products from composite materials is the interpretation and identification of recorded information during development processes occurring in the material’s structure. This is due to the high sensitivity of the acoustic emission method to various influencing factorsand the practical absence of acoustic radiation models. To solve this problem, it is necessary to determine the influence of various factors on acoustic radiation parameters. In this study, based on the acoustic radiation developed model we simulate the influence of one parameter characterizing composite properties on acoustic emission energy parameters during composite material destruction by shear forces according to the von Mises criterion. Simulation of acoustic radiation under given conditions makes it possible to determine the patterns of acoustic emission signals energy parameters changes and their sensitivity to changes of influencing factor, as well as to obtain mathematical expressions for describing obtained patterns. The results of this case study can be useful for developing methods of control, monitoring and diagnostics of composite materials and products made from composite materials.
{"title":"Amplitude-Energy Parameters of Acoustic Radiation with Composite Properties Changing and Mieses Destruction","authors":"Sergii Filonenko, Anzhelika Stakhova","doi":"10.14313/jamris/4-2022/29","DOIUrl":"https://doi.org/10.14313/jamris/4-2022/29","url":null,"abstract":"Abstract The main problem with using acoustic emission to control and diagnostics of composite materials and products from composite materials is the interpretation and identification of recorded information during development processes occurring in the material’s structure. This is due to the high sensitivity of the acoustic emission method to various influencing factorsand the practical absence of acoustic radiation models. To solve this problem, it is necessary to determine the influence of various factors on acoustic radiation parameters. In this study, based on the acoustic radiation developed model we simulate the influence of one parameter characterizing composite properties on acoustic emission energy parameters during composite material destruction by shear forces according to the von Mises criterion. Simulation of acoustic radiation under given conditions makes it possible to determine the patterns of acoustic emission signals energy parameters changes and their sensitivity to changes of influencing factor, as well as to obtain mathematical expressions for describing obtained patterns. The results of this case study can be useful for developing methods of control, monitoring and diagnostics of composite materials and products made from composite materials.","PeriodicalId":37910,"journal":{"name":"Journal of Automation, Mobile Robotics and Intelligent Systems","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135830220","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 this paper, our focus is on predicting the severity of traffic accidents, which represents a significant advancement in road accident management. Addressing this issue holds crucial implications for emergency logistical planning within urban areas. To assess accident severity within congested settings, we analyze the potential consequences of accidents, aiming to enhance the effectiveness of accident management protocols. In the context of this study, we introduce a real-time big data project. Our approach involves the implementation and comparison of various machine learning algorithms, namely Random Forest, Support Vector Machine (SVM), and Artificial Neural Network (ANN). The objective is to accurately classify and predict the severity of traffic accidents. Our methodology revolves around the real-time capture of incoming datasets, which are then stored within a Hadoop Distributed File System cluster. Subsequently, we leverage the core functionality of Spark MLlib, making use of pre-implemented Lambda functions. Throughout the project, classification and recognition tasks are conducted as part of the data locality processing paradigm. To validate our approach, we utilize a confusion matrix, which enables us to gauge the interclass impacts among Pedestrians, Vehicles or pillion passengers, and Drivers or riders. For empirical validation, we employ the TRAFFIC ACCIDENTS_2019_LEEDS dataset sourced from the Road Safety Department of Transport. This dataset facilitates the classification of severity predictions into three distinct categories: Pedestrian, vehicle or pillion passenger, and driver or rider. Notably, our experiments reveal impressive results. The Random Forest algorithm achieves an accuracy rate of 93%, outperforming SVM at 82% and ANN at 87%. Furthermore, in terms of precision-recall metrics, Random Forest also excels with a score of 93.82%, compared to SVM's 82.22% and ANN's 87.88%.
{"title":"A Distributed Big Data Analytics Models for Traffic Accidents Classification and Recognition based SparkMlLib Cores","authors":"Imad El Mallahi, Jamal Riffi, Hamid Tairi, Abderrahamane Ez-Zahout, Mohamed Adnane Mahraz","doi":"10.14313/jamris/4-2022/34","DOIUrl":"https://doi.org/10.14313/jamris/4-2022/34","url":null,"abstract":"In this paper, our focus is on predicting the severity of traffic accidents, which represents a significant advancement in road accident management. Addressing this issue holds crucial implications for emergency logistical planning within urban areas. To assess accident severity within congested settings, we analyze the potential consequences of accidents, aiming to enhance the effectiveness of accident management protocols. In the context of this study, we introduce a real-time big data project. Our approach involves the implementation and comparison of various machine learning algorithms, namely Random Forest, Support Vector Machine (SVM), and Artificial Neural Network (ANN). The objective is to accurately classify and predict the severity of traffic accidents. Our methodology revolves around the real-time capture of incoming datasets, which are then stored within a Hadoop Distributed File System cluster. Subsequently, we leverage the core functionality of Spark MLlib, making use of pre-implemented Lambda functions. Throughout the project, classification and recognition tasks are conducted as part of the data locality processing paradigm. To validate our approach, we utilize a confusion matrix, which enables us to gauge the interclass impacts among Pedestrians, Vehicles or pillion passengers, and Drivers or riders. For empirical validation, we employ the TRAFFIC ACCIDENTS_2019_LEEDS dataset sourced from the Road Safety Department of Transport. This dataset facilitates the classification of severity predictions into three distinct categories: Pedestrian, vehicle or pillion passenger, and driver or rider. Notably, our experiments reveal impressive results. The Random Forest algorithm achieves an accuracy rate of 93%, outperforming SVM at 82% and ANN at 87%. Furthermore, in terms of precision-recall metrics, Random Forest also excels with a score of 93.82%, compared to SVM's 82.22% and ANN's 87.88%.","PeriodicalId":37910,"journal":{"name":"Journal of Automation, Mobile Robotics and Intelligent Systems","volume":"122 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135830225","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 article describes the hardware and software design of a vision-based autonomous turret system. A two degree of freedom (2 DOF) turret platform is designed to carry a canon equipped with an embedded camera and actuated by stepper motors or direct current motors. The turret system includes a central calculator running a visual detection and tracking solution, and a microcontroller, responsible for actuators control. The Tracking-Learning-Detection (TLD) algorithm is implemented for target detection and tracking. Furthermore, a Kalman filter algorithm is implemented to continue the tracking in case of occlusion. The performances of the designed turret, regarding response time, accuracy and the execution time of its main tasks, are evaluated. In addition, an experimental scenario was performed for real-time autonomous detection and tracking of a moving target.
{"title":"Design of a Vision Based Autonomous Turret","authors":"Rabah Louali, Djilali Negadi, Rabah Hamadouche, Abdelkrim Nemra","doi":"10.14313/jamris/4-2022/35","DOIUrl":"https://doi.org/10.14313/jamris/4-2022/35","url":null,"abstract":"This article describes the hardware and software design of a vision-based autonomous turret system. A two degree of freedom (2 DOF) turret platform is designed to carry a canon equipped with an embedded camera and actuated by stepper motors or direct current motors. The turret system includes a central calculator running a visual detection and tracking solution, and a microcontroller, responsible for actuators control. The Tracking-Learning-Detection (TLD) algorithm is implemented for target detection and tracking. Furthermore, a Kalman filter algorithm is implemented to continue the tracking in case of occlusion. The performances of the designed turret, regarding response time, accuracy and the execution time of its main tasks, are evaluated. In addition, an experimental scenario was performed for real-time autonomous detection and tracking of a moving target.","PeriodicalId":37910,"journal":{"name":"Journal of Automation, Mobile Robotics and Intelligent Systems","volume":"304 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135830048","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}
With the growing number of city vehicles, traffic management is becoming one of the most persistent challenges. Traffic bottlenecks cause more significant disturbances in our everyday lives and raise stress levels, negatively impacting the environment by increasing carbon emissions. Due to the population increase, megacities are experiencing severe challenges and significant delays in their day-to-day activities related to transportation. An intelligent traffic management system is required to assess traffic density regularly and take appropriate action. Even though separate lanes are available for various vehicle types, the effective result of wait times for the Commuters at the traffic signal point is not reduced. The proposed methodology employs Artificial Intelligence to collect live images from signals to address this issue in the current system. This approach calculates traffic density, utilizing the image processing technique YOLOv4 for effective traffic congestion management. The YOLOv4 algorithm produces better accuracy in the detection of multiple vehicles. Intelligent monitoring technology uses a signal-switching algorithm at signal intersections to coordinate time distribution and alleviate traffic congestion, resulting in lower vehicle waiting times.
{"title":"AI-based YOLO V4 Intelligent Traffic Light Control System","authors":"Prathap Rudra Boppuru, Pradeep Kumar Kukatlapalli, Cherukuri Ravindranath Chowdary, Javid Hussain","doi":"10.14313/jamris/4-2022/33","DOIUrl":"https://doi.org/10.14313/jamris/4-2022/33","url":null,"abstract":"With the growing number of city vehicles, traffic management is becoming one of the most persistent challenges. Traffic bottlenecks cause more significant disturbances in our everyday lives and raise stress levels, negatively impacting the environment by increasing carbon emissions. Due to the population increase, megacities are experiencing severe challenges and significant delays in their day-to-day activities related to transportation. An intelligent traffic management system is required to assess traffic density regularly and take appropriate action. Even though separate lanes are available for various vehicle types, the effective result of wait times for the Commuters at the traffic signal point is not reduced. The proposed methodology employs Artificial Intelligence to collect live images from signals to address this issue in the current system. This approach calculates traffic density, utilizing the image processing technique YOLOv4 for effective traffic congestion management. The YOLOv4 algorithm produces better accuracy in the detection of multiple vehicles. Intelligent monitoring technology uses a signal-switching algorithm at signal intersections to coordinate time distribution and alleviate traffic congestion, resulting in lower vehicle waiting times.","PeriodicalId":37910,"journal":{"name":"Journal of Automation, Mobile Robotics and Intelligent Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135830050","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}
Pub Date : 2023-10-02DOI: 10.14313/jamris/4-2022/28
Luis Eduardo Garcia Linares, Esteban Rosero García
In this paper, the design and implementation of a non-linear model-based predictive controller (NMPC) for predefined trajectory tracking and to minimize the control effort of a smartphone-based quadrotor is carried out. The optimal control actions are calculated in each iteration by means of an optimal control algorithm based on the non-linear model of the quadrotor, considering some aerodynamic effects. Control algorithm implementation and simulation tests are executed on a smartphone using the CasADi framework. In addition, a technique for estimating the energy consumed based on control signals is presented. NMPC controller performance is compared to an H-infinity controller and an LQI controller, using three predefined trajectories, where the NMPC average tracking error was around 50% lower, and average estimated power and energy consumption slightly higher, with respect to the H-infinity and LQI controllers.
{"title":"Non-linear Model-based Predictive Control for Trajectory Tracking and Control Effort Minimization in a Smartphone-based Quadrotor","authors":"Luis Eduardo Garcia Linares, Esteban Rosero García","doi":"10.14313/jamris/4-2022/28","DOIUrl":"https://doi.org/10.14313/jamris/4-2022/28","url":null,"abstract":"In this paper, the design and implementation of a non-linear model-based predictive controller (NMPC) for predefined trajectory tracking and to minimize the control effort of a smartphone-based quadrotor is carried out. The optimal control actions are calculated in each iteration by means of an optimal control algorithm based on the non-linear model of the quadrotor, considering some aerodynamic effects. Control algorithm implementation and simulation tests are executed on a smartphone using the CasADi framework. In addition, a technique for estimating the energy consumed based on control signals is presented. NMPC controller performance is compared to an H-infinity controller and an LQI controller, using three predefined trajectories, where the NMPC average tracking error was around 50% lower, and average estimated power and energy consumption slightly higher, with respect to the H-infinity and LQI controllers.","PeriodicalId":37910,"journal":{"name":"Journal of Automation, Mobile Robotics and Intelligent Systems","volume":"304 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135830058","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}
Pub Date : 2023-05-23DOI: 10.14313/jamris/2-2022/14
Ramalingam Sengalani, Rasool Mohideen S
In this research, a model of a robotic manipulator flexible structure and an equation of motion for controller design is planned. The structural material for the robot structure is chosen as a hybrid composite for this investigation along with a comparison study is carried out for the aluminium 6082 alloy of flexible manipulator arm application. To analyses, the vibration behavior and control implementation by adding joint flexibility in the system is organized. Using simulation algorithm, system parameter calculation is carried out through MATLAB software for vibration amplitude, transient period, steady-state error, and settling time of flexible robotic arm system. In a systematized way of motion equation, flexible robotic deflections are organized via the assumed mode (AM) and Lagrange techniques (LT). The graph analysis of hybrid composite and AL6082 materials with high stiffness coefficients is plotted. These obtained values from the plot are utilized for Linear Quadratic Regulator (LQR) controller design. The LQR output facts for both aluminium structural robotic arm and composite material robotic arms are established.
{"title":"Vibration Control Using Modern Control System for Hybrid Composite Flexible Robot Manipulator Arm","authors":"Ramalingam Sengalani, Rasool Mohideen S","doi":"10.14313/jamris/2-2022/14","DOIUrl":"https://doi.org/10.14313/jamris/2-2022/14","url":null,"abstract":"In this research, a model of a robotic manipulator flexible structure and an equation of motion for controller design is planned. The structural material for the robot structure is chosen as a hybrid composite for this investigation along with a comparison study is carried out for the aluminium 6082 alloy of flexible manipulator arm application. To analyses, the vibration behavior and control implementation by adding joint flexibility in the system is organized. Using simulation algorithm, system parameter calculation is carried out through MATLAB software for vibration amplitude, transient period, steady-state error, and settling time of flexible robotic arm system. In a systematized way of motion equation, flexible robotic deflections are organized via the assumed mode (AM) and Lagrange techniques (LT). The graph analysis of hybrid composite and AL6082 materials with high stiffness coefficients is plotted. These obtained values from the plot are utilized for Linear Quadratic Regulator (LQR) controller design. The LQR output facts for both aluminium structural robotic arm and composite material robotic arms are established.","PeriodicalId":37910,"journal":{"name":"Journal of Automation, Mobile Robotics and Intelligent Systems","volume":"51 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84691975","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}
Pub Date : 2022-09-28DOI: 10.14313/jamris/4-2021/25
Jinsiang Shaw, Yu Fang
In traditional industries, manual grinding and polishing technologies are still used predominantly. However, these procedures have the following limitations: excessive processing time, labor consumption, and product quality not guaranteed. To address the aforementioned limitations, this study utilizes the good adaptability of a robotic arm to develop a tool-holding grinding and polishing system with force control mechanisms. Specifically, off-the-shelf handheld grinder is selected and attached to the robotic arm by considering the size, weight, and processing cost of the stainless steel parts. In addition, for contact machining, the robotic arm is equipped with a force/torque sensor to ensure that the system is active compliant. According to the experimental results, the developed system can reduce the surface roughness of 304 stainless steel to 0.47 µm for flat surface and 0.76 µm for circular surface. Moreover, the processing trajectory is programmed in the CAD/CAM software simulation environment, which can lead to good results in collision detection and arm posture establishment.
{"title":"Development of Grinding and Polishing Technology for Stainless Steel With a Robot Manipulator","authors":"Jinsiang Shaw, Yu Fang","doi":"10.14313/jamris/4-2021/25","DOIUrl":"https://doi.org/10.14313/jamris/4-2021/25","url":null,"abstract":"In traditional industries, manual grinding and polishing technologies are still used predominantly. However, these procedures have the following limitations: excessive processing time, labor consumption, and product quality not guaranteed. To address the aforementioned limitations, this study utilizes the good adaptability of a robotic arm to develop a tool-holding grinding and polishing system with force control mechanisms. Specifically, off-the-shelf handheld grinder is selected and attached to the robotic arm by considering the size, weight, and processing cost of the stainless steel parts. In addition, for contact machining, the robotic arm is equipped with a force/torque sensor to ensure that the system is active compliant. According to the experimental results, the developed system can reduce the surface roughness of 304 stainless steel to 0.47 µm for flat surface and 0.76 µm for circular surface. Moreover, the processing trajectory is programmed in the CAD/CAM software simulation environment, which can lead to good results in collision detection and arm posture establishment.","PeriodicalId":37910,"journal":{"name":"Journal of Automation, Mobile Robotics and Intelligent Systems","volume":"168 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83645528","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：