R. Iinuma, Yusuke Hori, Hiroyuki Onoyama, Y. Kubo, T. Fukao
We propose a robotic forklift system for stacking multiple mesh pallets. The stacking of mesh pallets is an essential task for the shipping and storage of loads. However, stacking, the placement of pallet feet on pallet edges, is a complex problem owing to the small sizes of the feet and edges, leading to a complexity in the detection and the need for high accuracy in adjusting the pallets. To detect the pallets accurately, we utilize multiple RGB-D (RGB Depth) cameras that produce dense depth data under the limitations of the sensor position. However, the depth data contain noise. Hence, we implement a region growing-based algorithm to extract the pallet feet and edges without removing them. In addition, we design the control law based on path following control for the forklift to adjust the position and orientation of two pallets. To evaluate the performance of the proposed system, we conducted an experiment assuming a real task. The experimental results demonstrated that the proposed system can achieve a stacking operation with a real forklift and mesh pallets.
我们提出了一种机器人叉车系统，用于堆叠多个网格托盘。网状托盘的堆垛是货物运输和储存的一项重要任务。然而，由于托盘脚和托盘边缘的尺寸较小，托盘脚在托盘边缘上的放置是一个复杂的问题，导致检测的复杂性和对托盘调整精度的要求很高。为了准确地检测托盘，我们利用多个RGB- d (RGB深度)相机，在传感器位置的限制下产生密集的深度数据。然而，深度数据包含噪声。因此，我们实现了一种基于区域生长的算法来提取托盘脚和边缘而不移除它们。此外，我们设计了基于路径跟随控制的叉车控制律，以调整两个托盘的位置和方向。为了评估所提出的系统的性能，我们进行了一个假设真实任务的实验。实验结果表明，该系统可以实现真实叉车和网状托盘的堆垛作业。
{"title":"Robotic Forklift for Stacking Multiple Pallets with RGB-D Cameras","authors":"R. Iinuma, Yusuke Hori, Hiroyuki Onoyama, Y. Kubo, T. Fukao","doi":"10.20965/jrm.2021.p1265","DOIUrl":"https://doi.org/10.20965/jrm.2021.p1265","url":null,"abstract":"We propose a robotic forklift system for stacking multiple mesh pallets. The stacking of mesh pallets is an essential task for the shipping and storage of loads. However, stacking, the placement of pallet feet on pallet edges, is a complex problem owing to the small sizes of the feet and edges, leading to a complexity in the detection and the need for high accuracy in adjusting the pallets. To detect the pallets accurately, we utilize multiple RGB-D (RGB Depth) cameras that produce dense depth data under the limitations of the sensor position. However, the depth data contain noise. Hence, we implement a region growing-based algorithm to extract the pallet feet and edges without removing them. In addition, we design the control law based on path following control for the forklift to adjust the position and orientation of two pallets. To evaluate the performance of the proposed system, we conducted an experiment assuming a real task. The experimental results demonstrated that the proposed system can achieve a stacking operation with a real forklift and mesh pallets.","PeriodicalId":51661,"journal":{"name":"Journal of Robotics and Mechatronics","volume":"33 1","pages":"1265-1273"},"PeriodicalIF":1.1,"publicationDate":"2021-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68078612","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}
Hydraulic excavators are one type of construction equipment used in various construction sites worldwide, and their usage and scale are diverse. Generally, the work efficiency of a hydraulic excavator largely depends on human operation skills. If we can comprehend the experienced operation skills and utilize them for manual control assist, semi-automatic or automatic remote control, it would improve its work efficiency and suppress personnel costs, reduce the operator’s workload, and improve his/her safety. In this study, we propose a methodology to design efficient machine trajectories based on mathematical models and numerical optimization, focusing on ground-level excavation as a dominant task. First, we express its excavation trajectory using four parameters and assume the models for the amount of excavated soil and the reaction force based on our previous experiments. Next, we combine these models with a geometrical model for the hydraulic excavating machine. We then assign the amount of soil to a performance index preferably to be maximized and the amount of work to a cost index preferably to be minimized, both in the form of functions of the trajectory parameters, resulting in an optimization problem that trades them off. In particular, we formulate (1) a multi-objective optimization problem maximizing a weighted linear combination of the amount of soil and the amount of work as an objective function, and (2) a single-objective optimization problem maximizing the amount of soil under a given upper bound on the amount of work, so that we can solve these optimization problems using the genetic algorithm (GA). Finally, we conclude this paper by suggesting our notice on design methodology and discussing how we should provide the optimization method as mentioned above to the users who operate hydraulic excavators.
{"title":"An Optimal Design Methodology for the Trajectory of Hydraulic Excavators Based on Genetic Algorithm","authors":"Takamichi Yuasa, M. Ishikawa, Satoshi Ogawa","doi":"10.20965/jrm.2021.p1248","DOIUrl":"https://doi.org/10.20965/jrm.2021.p1248","url":null,"abstract":"Hydraulic excavators are one type of construction equipment used in various construction sites worldwide, and their usage and scale are diverse. Generally, the work efficiency of a hydraulic excavator largely depends on human operation skills. If we can comprehend the experienced operation skills and utilize them for manual control assist, semi-automatic or automatic remote control, it would improve its work efficiency and suppress personnel costs, reduce the operator’s workload, and improve his/her safety. In this study, we propose a methodology to design efficient machine trajectories based on mathematical models and numerical optimization, focusing on ground-level excavation as a dominant task. First, we express its excavation trajectory using four parameters and assume the models for the amount of excavated soil and the reaction force based on our previous experiments. Next, we combine these models with a geometrical model for the hydraulic excavating machine. We then assign the amount of soil to a performance index preferably to be maximized and the amount of work to a cost index preferably to be minimized, both in the form of functions of the trajectory parameters, resulting in an optimization problem that trades them off. In particular, we formulate (1) a multi-objective optimization problem maximizing a weighted linear combination of the amount of soil and the amount of work as an objective function, and (2) a single-objective optimization problem maximizing the amount of soil under a given upper bound on the amount of work, so that we can solve these optimization problems using the genetic algorithm (GA). Finally, we conclude this paper by suggesting our notice on design methodology and discussing how we should provide the optimization method as mentioned above to the users who operate hydraulic excavators.","PeriodicalId":51661,"journal":{"name":"Journal of Robotics and Mechatronics","volume":"33 1","pages":"1248-1254"},"PeriodicalIF":1.1,"publicationDate":"2021-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68077445","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}
Alfin Junaedy, H. Masuta, K. Sawai, T. Motoyoshi, Noboru Takagi
In this study, the teleoperation robot control on a mobile robot with 2D SLAM and object localization using LPWAN is proposed. The mobile robot is a technology gaining popularity due to flexibility and robustness in a variety of terrains. In search and rescue activities, the mobile robots can be used to perform some missions, assist and preserve human life. However, teleoperation control becomes a challenging problem for this implementation. The robust wireless communication not only allows the operator to stay away from dangerous area, but also increases the mobility of the mobile robot itself. Most of teleoperation mobile robots use Wi-Fi having high-bandwidth, yet short communication range. LoRa as LPWAN, on the other hand, has much longer range but low-bandwidth communication speed. Therefore, the combination of them complements each other’s weaknesses. The use of a two-LoRa configuration also enhances the teleoperation capabilities. All information from the mobile robot can be sent to the PC controller in relatively fast enough for real-time SLAM implementation. Furthermore, the mobile robot is also capable of real-time object detection, localization, and transmitting images. Another problem of LoRa communication is a timeout. We apply timeout recovery algorithms to handle this issue, resulting in more stable data. All data have been confirmed by real-time trials and the proposed method can approach the Wi-Fi performance with a low waiting time or delay.
{"title":"LPWAN-Based Real-Time 2D SLAM and Object Localization for Teleoperation Robot Control","authors":"Alfin Junaedy, H. Masuta, K. Sawai, T. Motoyoshi, Noboru Takagi","doi":"10.20965/jrm.2021.p1326","DOIUrl":"https://doi.org/10.20965/jrm.2021.p1326","url":null,"abstract":"In this study, the teleoperation robot control on a mobile robot with 2D SLAM and object localization using LPWAN is proposed. The mobile robot is a technology gaining popularity due to flexibility and robustness in a variety of terrains. In search and rescue activities, the mobile robots can be used to perform some missions, assist and preserve human life. However, teleoperation control becomes a challenging problem for this implementation. The robust wireless communication not only allows the operator to stay away from dangerous area, but also increases the mobility of the mobile robot itself. Most of teleoperation mobile robots use Wi-Fi having high-bandwidth, yet short communication range. LoRa as LPWAN, on the other hand, has much longer range but low-bandwidth communication speed. Therefore, the combination of them complements each other’s weaknesses. The use of a two-LoRa configuration also enhances the teleoperation capabilities. All information from the mobile robot can be sent to the PC controller in relatively fast enough for real-time SLAM implementation. Furthermore, the mobile robot is also capable of real-time object detection, localization, and transmitting images. Another problem of LoRa communication is a timeout. We apply timeout recovery algorithms to handle this issue, resulting in more stable data. All data have been confirmed by real-time trials and the proposed method can approach the Wi-Fi performance with a low waiting time or delay.","PeriodicalId":51661,"journal":{"name":"Journal of Robotics and Mechatronics","volume":"33 1","pages":"1326-1337"},"PeriodicalIF":1.1,"publicationDate":"2021-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68078607","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 paper discusses a camera-based velocity estimation for unmanned ground vehicles in an agriculture scale. The proposed concept-based method does not require any geometric feature and focuses on a mapping between the captured images only. The paper provides three pilot experiments. First, we check an assumption of the proposed concept by a field experiment. Second, we check the verification by a set of numerical and laboratory experiments. Third, we check the verification by the field experiment. In the sense that the existence and sensitivity of a representation of the mapping are verified experimentally, the feasibility of the proposed concept is confirmed.
{"title":"On the Geometric Featureless Visual Velocity of UGV in an Agriculture Scale","authors":"S. Sakai, Daiki Nakabayashi","doi":"10.20965/jrm.2021.p1255","DOIUrl":"https://doi.org/10.20965/jrm.2021.p1255","url":null,"abstract":"The paper discusses a camera-based velocity estimation for unmanned ground vehicles in an agriculture scale. The proposed concept-based method does not require any geometric feature and focuses on a mapping between the captured images only. The paper provides three pilot experiments. First, we check an assumption of the proposed concept by a field experiment. Second, we check the verification by a set of numerical and laboratory experiments. Third, we check the verification by the field experiment. In the sense that the existence and sensitivity of a representation of the mapping are verified experimentally, the feasibility of the proposed concept is confirmed.","PeriodicalId":51661,"journal":{"name":"Journal of Robotics and Mechatronics","volume":"33 1","pages":"1255-1264"},"PeriodicalIF":1.1,"publicationDate":"2021-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68078412","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}
Alireza Bilesan, S. Komizunai, T. Tsujita, A. Konno
Kinect has been utilized as a cost-effective, easy-to-use motion capture sensor using the Kinect skeleton algorithm. However, a limited number of landmarks and inaccuracies in tracking the landmarks’ positions restrict Kinect’s capability. In order to increase the accuracy of motion capturing using Kinect, joint use of the Kinect skeleton algorithm and Kinect-based marker tracking was applied to track the 3D coordinates of multiple landmarks on human. The motion’s kinematic parameters were calculated using the landmarks’ positions by applying the joint constraints and inverse kinematics techniques. The accuracy of the proposed method and OptiTrack (NaturalPoint, Inc., USA) was evaluated in capturing the joint angles of a humanoid (as ground truth) in a walking test. In order to evaluate the accuracy of the proposed method in capturing the kinematic parameters of a human, lower body joint angles of five healthy subjects were extracted using a Kinect, and the results were compared to Perception Neuron (Noitom Ltd., China) and OptiTrack data during ten gait trials. The absolute agreement and consistency between each optical system and the robot data in the robot test and between each motion capture system and OptiTrack data in the human gait test were determined using intraclass correlations coefficients (ICC3). The reproducibility between systems was evaluated using Lin’s concordance correlation coefficient (CCC). The correlation coefficients with 95% confidence intervals (95%CI) were interpreted substantial for both OptiTrack and proposed method (ICC > 0.75 and CCC > 0.95) in humanoid test. The results of the human gait experiments demonstrated the advantage of the proposed method (ICC > 0.75 and RMSE = 1.1460°) over the Kinect skeleton model (ICC < 0.4 and RMSE = 6.5843°).
{"title":"Improved 3D Human Motion Capture Using Kinect Skeleton and Depth Sensor","authors":"Alireza Bilesan, S. Komizunai, T. Tsujita, A. Konno","doi":"10.20965/jrm.2021.p1408","DOIUrl":"https://doi.org/10.20965/jrm.2021.p1408","url":null,"abstract":"Kinect has been utilized as a cost-effective, easy-to-use motion capture sensor using the Kinect skeleton algorithm. However, a limited number of landmarks and inaccuracies in tracking the landmarks’ positions restrict Kinect’s capability. In order to increase the accuracy of motion capturing using Kinect, joint use of the Kinect skeleton algorithm and Kinect-based marker tracking was applied to track the 3D coordinates of multiple landmarks on human. The motion’s kinematic parameters were calculated using the landmarks’ positions by applying the joint constraints and inverse kinematics techniques. The accuracy of the proposed method and OptiTrack (NaturalPoint, Inc., USA) was evaluated in capturing the joint angles of a humanoid (as ground truth) in a walking test. In order to evaluate the accuracy of the proposed method in capturing the kinematic parameters of a human, lower body joint angles of five healthy subjects were extracted using a Kinect, and the results were compared to Perception Neuron (Noitom Ltd., China) and OptiTrack data during ten gait trials. The absolute agreement and consistency between each optical system and the robot data in the robot test and between each motion capture system and OptiTrack data in the human gait test were determined using intraclass correlations coefficients (ICC3). The reproducibility between systems was evaluated using Lin’s concordance correlation coefficient (CCC). The correlation coefficients with 95% confidence intervals (95%CI) were interpreted substantial for both OptiTrack and proposed method (ICC > 0.75 and CCC > 0.95) in humanoid test. The results of the human gait experiments demonstrated the advantage of the proposed method (ICC > 0.75 and RMSE = 1.1460°) over the Kinect skeleton model (ICC < 0.4 and RMSE = 6.5843°).","PeriodicalId":51661,"journal":{"name":"Journal of Robotics and Mechatronics","volume":"33 1","pages":"1408-1422"},"PeriodicalIF":1.1,"publicationDate":"2021-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68079778","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}
Yoshiyuki Higashi, Kenta Yamazaki, A. Masuda, N. Miura, Y. Sawada
This paper presents an attractive force estimation system and an automatic activation system for an electropermanent magnet (EPM) for an inspection UAV. Adsorption to infrastructures for inspection at a distance is extremely difficult to perform safely because the operator cannot detect the state of adsorption of the drone equipped with a magnetic adsorption device. Therefore, in this paper, we clarify the relationship between the magnetic flux density and attractive force of the EPM through experiments, and develop an estimation algorithm for the attractive force based on the results. An automatic activation system, using the induced voltage in the coil when the EPM approaches the magnetic substance, is developed and mounted on a quadrotor for a flight experiment along with the estimation system for the attractive force. The developed system is verified using flight and adsorption experiments on the quadrotor.
{"title":"Attractive Force Estimation of a Magnetic Adsorption Unit for Inspection UAVs","authors":"Yoshiyuki Higashi, Kenta Yamazaki, A. Masuda, N. Miura, Y. Sawada","doi":"10.20965/jrm.2021.p1349","DOIUrl":"https://doi.org/10.20965/jrm.2021.p1349","url":null,"abstract":"This paper presents an attractive force estimation system and an automatic activation system for an electropermanent magnet (EPM) for an inspection UAV. Adsorption to infrastructures for inspection at a distance is extremely difficult to perform safely because the operator cannot detect the state of adsorption of the drone equipped with a magnetic adsorption device. Therefore, in this paper, we clarify the relationship between the magnetic flux density and attractive force of the EPM through experiments, and develop an estimation algorithm for the attractive force based on the results. An automatic activation system, using the induced voltage in the coil when the EPM approaches the magnetic substance, is developed and mounted on a quadrotor for a flight experiment along with the estimation system for the attractive force. The developed system is verified using flight and adsorption experiments on the quadrotor.","PeriodicalId":51661,"journal":{"name":"Journal of Robotics and Mechatronics","volume":"33 1","pages":"1349-1358"},"PeriodicalIF":1.1,"publicationDate":"2021-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68079600","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 describes the development of a robust object tracking system that combines detection methods based on image processing and machine learning for automatic construction machine tracking cameras at unmanned construction sites. In recent years, unmanned construction technology has been developed to prevent secondary disasters from harming workers in hazardous areas. There are surveillance cameras on disaster sites that monitor the environment and movements of construction machines. By watching footage from the surveillance cameras, machine operators can control the construction machines from a safe remote site. However, to control surveillance cameras to follow the target machines, camera operators are also required to work next to machine operators. To improve efficiency, an automatic tracking camera system for construction machines is required. We propose a robust and scalable object tracking system and robust object detection algorithm, and present an accurate and robust tracking system for construction machines by integrating these two methods. Our proposed image-processing algorithm is able to continue tracking for a longer period than previous methods, and the proposed object detection method using machine learning detects machines robustly by focusing on their component parts of the target objects. Evaluations in real-world field scenarios demonstrate that our methods are more accurate and robust than existing off-the-shelf object tracking algorithms while maintaining practical real-time processing performance.
{"title":"Development of an Automatic Tracking Camera System Integrating Image Processing and Machine Learning","authors":"Masato Fujitake, Makito Inoue, T. Yoshimi","doi":"10.20965/jrm.2021.p1303","DOIUrl":"https://doi.org/10.20965/jrm.2021.p1303","url":null,"abstract":"This paper describes the development of a robust object tracking system that combines detection methods based on image processing and machine learning for automatic construction machine tracking cameras at unmanned construction sites. In recent years, unmanned construction technology has been developed to prevent secondary disasters from harming workers in hazardous areas. There are surveillance cameras on disaster sites that monitor the environment and movements of construction machines. By watching footage from the surveillance cameras, machine operators can control the construction machines from a safe remote site. However, to control surveillance cameras to follow the target machines, camera operators are also required to work next to machine operators. To improve efficiency, an automatic tracking camera system for construction machines is required. We propose a robust and scalable object tracking system and robust object detection algorithm, and present an accurate and robust tracking system for construction machines by integrating these two methods. Our proposed image-processing algorithm is able to continue tracking for a longer period than previous methods, and the proposed object detection method using machine learning detects machines robustly by focusing on their component parts of the target objects. Evaluations in real-world field scenarios demonstrate that our methods are more accurate and robust than existing off-the-shelf object tracking algorithms while maintaining practical real-time processing performance.","PeriodicalId":51661,"journal":{"name":"Journal of Robotics and Mechatronics","volume":"33 1","pages":"1303-1314"},"PeriodicalIF":1.1,"publicationDate":"2021-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68078478","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}
Field robotics has been undergoing rapid progress in recent years. It addresses a wide range of activities performed in outdoor environments, and its applications are being developed in areas where it was previously considered difficult to apply. This rapid progress is largely supported by AI-based improvements in computer vision systems with monocular cameras, stereo cameras, RGB-D cameras, LiDAR systems, and/or other sensors. Field robotics is impelled by an application-driven approach by its nature, and it contributes to the resolution of social problems and the creation of new innovations, including autonomous driving to reduce casualties, autonomous working machines/robots to resolve the problems of labor shortages or dangers, disaster-response robots to aid rescue parties, various kinds of aerial robots to do searches or make deliveries, underwater robots to perform search missions, etc. In this special issue on “Field Robotics with Vision Systems,” we highlight sixteen interesting papers, including one review paper, fourteen research papers, and one development report. They cover various application areas, ranging from underwater to space environments, and they propose interesting integration methods or element technologies to use in outdoor environments where vision systems and robot systems have great difficulty performing robustly. We thank all authors and reviewers, and we hope that this special issue contributes to future research and development in area of field robotics, which promises new innovations.
{"title":"Special Issue on Field Robotics with Vision Systems","authors":"T. Fukao, Y. Tsumaki, K. Kurashiki","doi":"10.20965/jrm.2021.p1215","DOIUrl":"https://doi.org/10.20965/jrm.2021.p1215","url":null,"abstract":"Field robotics has been undergoing rapid progress in recent years. It addresses a wide range of activities performed in outdoor environments, and its applications are being developed in areas where it was previously considered difficult to apply. This rapid progress is largely supported by AI-based improvements in computer vision systems with monocular cameras, stereo cameras, RGB-D cameras, LiDAR systems, and/or other sensors. Field robotics is impelled by an application-driven approach by its nature, and it contributes to the resolution of social problems and the creation of new innovations, including autonomous driving to reduce casualties, autonomous working machines/robots to resolve the problems of labor shortages or dangers, disaster-response robots to aid rescue parties, various kinds of aerial robots to do searches or make deliveries, underwater robots to perform search missions, etc.\u0000 In this special issue on “Field Robotics with Vision Systems,” we highlight sixteen interesting papers, including one review paper, fourteen research papers, and one development report. They cover various application areas, ranging from underwater to space environments, and they propose interesting integration methods or element technologies to use in outdoor environments where vision systems and robot systems have great difficulty performing robustly.\u0000 We thank all authors and reviewers, and we hope that this special issue contributes to future research and development in area of field robotics, which promises new innovations.","PeriodicalId":51661,"journal":{"name":"Journal of Robotics and Mechatronics","volume":"33 1","pages":"1215"},"PeriodicalIF":1.1,"publicationDate":"2021-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68077584","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 : 2021-01-01DOI: 10.3844/jmrsp.2021.23.32
P. Chand, Joven Sepulveda
Corresponding Author: Praneel Chand Centre for Engineering and Industrial Design, Waikato Institute of Technology, Hamilton, New Zealand Email: praneelchand10@yahoo.co.nz Abstract: Industry equipment such as machinery utilising Programmable Logic Controllers (PLCs) become outdated and obsolete over time. Support for older machines and controllers becomes limited and they become incompatible with new computer operating systems. In the end, they are no longer used by industry. However, obsolete machines can be refurbished and used for teaching or demonstration purposes. Hence, this study presents the reconditioning of a Festo manufacturing machine by replacing the old Festo PLC with an Allen-Bradley PLC so that it’s compatible with the miniindustrial network in the mechatronics lab. The machine is a Festo MPS storage and retrieval station featuring three axis electromechanical gantries, a gripper, DC motors with encoder feedback, reed switches and a pneumatic actuator. The I/O connections from these components to the old PLC is traced and a new interface to the Allen-Bradley PLC is established while keeping connectivity with the old Festo PLC for legacy control. This upgrade allows the machine to be used for student training in the automation courses. It also leaves an option for utilising the old Festo PLC if needed. A sample program has been developed to test and verify correct interfacing and operation of the Allen-Bradley PLC and Festo storage and retrieval station.
{"title":"Automating a Festo Manufacturing Machine with an Allen-Bradley PLC","authors":"P. Chand, Joven Sepulveda","doi":"10.3844/jmrsp.2021.23.32","DOIUrl":"https://doi.org/10.3844/jmrsp.2021.23.32","url":null,"abstract":"Corresponding Author: Praneel Chand Centre for Engineering and Industrial Design, Waikato Institute of Technology, Hamilton, New Zealand Email: praneelchand10@yahoo.co.nz Abstract: Industry equipment such as machinery utilising Programmable Logic Controllers (PLCs) become outdated and obsolete over time. Support for older machines and controllers becomes limited and they become incompatible with new computer operating systems. In the end, they are no longer used by industry. However, obsolete machines can be refurbished and used for teaching or demonstration purposes. Hence, this study presents the reconditioning of a Festo manufacturing machine by replacing the old Festo PLC with an Allen-Bradley PLC so that it’s compatible with the miniindustrial network in the mechatronics lab. The machine is a Festo MPS storage and retrieval station featuring three axis electromechanical gantries, a gripper, DC motors with encoder feedback, reed switches and a pneumatic actuator. The I/O connections from these components to the old PLC is traced and a new interface to the Allen-Bradley PLC is established while keeping connectivity with the old Festo PLC for legacy control. This upgrade allows the machine to be used for student training in the automation courses. It also leaves an option for utilising the old Festo PLC if needed. A sample program has been developed to test and verify correct interfacing and operation of the Allen-Bradley PLC and Festo storage and retrieval station.","PeriodicalId":51661,"journal":{"name":"Journal of Robotics and Mechatronics","volume":"5 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87485973","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 : 2021-01-01DOI: 10.3844/jmrsp.2021.33.46
N. Bailey, C. Lusty, P. Keogh
Corresponding Author: Nicola Yvonne Bailey Department of Mechanical Engineering, University of Bath, United Kingdom E-mail: n.y.bailey@bath.ac.uk Abstract: Automated machinery and robotics are commonly conventional multibody systems containing bearing components, which exhibit uncertain, discontinuous and complex tribological characteristics. These generate wear and fundamentally limit the precision of small scale motion due to the tribological effects being difficult to compensate for using model-based active control. However, they can be eliminated through the replacement of traditional bearing joints with flexure couplings, which offers a potential increase in the performance envelope. Initially a plain flexure coupling capable of large deformation is investigated, with a representative mathematical model derived based on large deformation Euler-Bernoulli theory which is validated using a bespoke experimental facility; proof of concept for the design of empirical controllers utilising experimental data is presented. Various designs of novel compound flexure couplings are conceived, comprising of multiple sections of spring steel. The presented compound flexure couplings are then characterised experimentally. A focused study of a two-compound flexure coupling-rigid body system is presented and the feasibility of generating open-loop feedfoward controllers from identified models is demonstrated in terms of accurate large displacement control. Including path correction in the presented control methodology reduces tracking errors by at least 62% and 71% in (x, y) directions, respectively, for the cases considered.
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