K. N. Kamaludin, L. Abdullah, S. Salim, Z. Jamaludin, T. H. Chiew, M. N. Kamarudin, M. Aras, M. F. Rahmat
{"title":"Performance Evaluation of an Adaptive Sigmoid Friction Compensation for Pneumatic Trajectory","authors":"K. N. Kamaludin, L. Abdullah, S. Salim, Z. Jamaludin, T. H. Chiew, M. N. Kamarudin, M. Aras, M. F. Rahmat","doi":"10.1109/ICCRE57112.2023.10155570","DOIUrl":"https://doi.org/10.1109/ICCRE57112.2023.10155570","url":null,"abstract":"Trajectory tracking is a challenging task in pneumatics due to the classification of the actuator as a nonlinear system. In addition to the said factor, nonlinear disturbances occur within the system, such as valve-dead zone, air compressibility, air density, internal valve and actuator friction. Actuators' internal friction is one of the most critical disturbances. For a near-zero velocity motion of an actuator, many scholars have designed and improved dynamic friction models for modeling and friction compensation. However, compensation using the dynamic model is complex and computationally exhaustive in real-time. Owing to this factor, a modified adaptive friction estimator and compensator are presented in this research. The adaptive sigmoid friction (FASF) function is designed to compensate both the pre-sliding and sliding regimes of the friction force. The function is coupled with a nonlinear hyperbolic PID (NPID+FASF) controller. The performance of the compensator was evaluated based on maximum tracking error (MTE), root mean square error (RMSE) and fast Fourier transform (FFT) error. The proposed NPID+FASF is observed to reduce all errors strategically. The improvement of MTE to the basic PID is up to 45.75%, RMSE of 27.88% and FFTE of 38.91%. To further improve the trajectory tracking performance, a ‘tracking differentiator’ has been proven to increase the performance of trajectory tracking and precise positioning.","PeriodicalId":285164,"journal":{"name":"2023 8th International Conference on Control and Robotics Engineering (ICCRE)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121834455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Simulation System of Underwater Manipulator Based on Gazebo","authors":"Ping Deng, Pu Zhang, Zheng Gong, Le Li","doi":"10.1109/ICCRE57112.2023.10155577","DOIUrl":"https://doi.org/10.1109/ICCRE57112.2023.10155577","url":null,"abstract":"Since the field experiment of underwater robots are costly and dangerous, simulation experiments are typically employed in the design and test process. This paper presents a quick and efficient technique for controlling the Moveit manipulator in a gazebo-based underwater simulation environment. First of all, a simulation system based on Gazebo is developed, which includes modeling the underwater environment, kinematics, the integration of gazebo and rviz, and the visualization of the entire configuration procedure. Next, the simulation experiments of the planning and movement of an underwater manipulator are conducted in an underwater setting. The experiment results demonstrate that the developed simulation system has visualized the motion of the underwater manipulator and collected the velocity and position of the joints during the simulation experiment.","PeriodicalId":285164,"journal":{"name":"2023 8th International Conference on Control and Robotics Engineering (ICCRE)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121962847","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}
Plaifah Laimek, W. Kongprawechnon, T. Phatrapornnant, T. Isshiki
{"title":"High-Value Fruit Biometric Identification via Triplet-Loss Technique","authors":"Plaifah Laimek, W. Kongprawechnon, T. Phatrapornnant, T. Isshiki","doi":"10.1109/ICCRE57112.2023.10155611","DOIUrl":"https://doi.org/10.1109/ICCRE57112.2023.10155611","url":null,"abstract":"High-valued products require an authentication method to provide the customers with a way to verify the product's genuineness. As the product's authenticity dramatically increases its value, the authentication method has to be reliable and secure. High-valued melon, a popular gift in Japan, is a suitable product for applying rind pattern identification, providing a new means of authenticity verification. As opposed to using only QR-code or RF-ID tags, implementing a rind pattern recognition can provide a more secure authentication method, improving customers' trust and further increasing the product value. A previous study on melon identification was done using a well-known method of fingerprint recognition known as minutiae feature extraction on the melon rind pattern. The study has shown accurate results in the controlled image acquisition environment. In this work, a method of melon identity matching is introduced by incorporating triplet loss function on a convolutional neural network, providing a system that can reliably match each melon image even with variating lighting, shadows, and angle.","PeriodicalId":285164,"journal":{"name":"2023 8th International Conference on Control and Robotics Engineering (ICCRE)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128988937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Industrial Modeling Design of Lower Limb Rehabilitation Robot System Based on AHP and Fuzzy Evaluation","authors":"Yuyu Shu, Yan Xing","doi":"10.1109/ICCRE57112.2023.10155603","DOIUrl":"https://doi.org/10.1109/ICCRE57112.2023.10155603","url":null,"abstract":"The lower limb rehabilitation robot emphasizes user experience more and more while restoring part of the patient's limb functions. Therefore, the main content of this paper is to make the lower limb rehabilitation robot more efficient, automated and human body coordinated. The purpose is to form a complete rehabilitation training, and the constructed system industrial modeling is more in line with the needs of ergonomics. This paper establishes a user model corresponding to the product. In this paper, the lower limb rehabilitation robot is divided into four parts: a cart, a robotic arm, a connecting end, and a rehabilitation device. We studied the usability features, shape, and CMF design elements of the four components. At the same time, for the four components of the lower limb rehabilitation robot, a specific design element requirements framework has been established. We use the method of combining AHP and fuzzy evaluation to redesign the original scheme, and evaluate the improved scheme and the original scheme. The improved scheme is more suitable for matching in size, more reliable, and more ergonomic in appearance.","PeriodicalId":285164,"journal":{"name":"2023 8th International Conference on Control and Robotics Engineering (ICCRE)","volume":"118 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132145827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An EMG-Based Teleoperation System with Small Hand Based on a Dual-Arm Task Model","authors":"T. Shibanoki, Kosuke Jin, Masaki Maeda","doi":"10.1109/ICCRE57112.2023.10155584","DOIUrl":"https://doi.org/10.1109/ICCRE57112.2023.10155584","url":null,"abstract":"This paper proposes an EMG-based small prosthetic hand for teleoperated tasks. In the proposed method, a small robot hand with five fingers, which is typical of mammals including humans, is made by a 3D printer and can be controlled according to the user's intended motions based on the discrimination results of the measured EMG signals. Tasks performed by the proposed system are described by a Petri net and each state generates a revised vector of discrimination results to assist the operation by dual-arm motion discrimination considering which motions should be used for each operation. The state transitions are performed by using dynamic and static information for both forearms simultaneously. In the experiment, the participant was asked to control the proposed system and could voluntarily manipulate the targeted tasks.","PeriodicalId":285164,"journal":{"name":"2023 8th International Conference on Control and Robotics Engineering (ICCRE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115203287","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}
Nilesh Aggarwal, Anunay, Vayam Jain, Tushar Singh, D. Vishwakarma
{"title":"DLVS: Time Series Architecture for Image-Based Visual Servoing","authors":"Nilesh Aggarwal, Anunay, Vayam Jain, Tushar Singh, D. Vishwakarma","doi":"10.1109/ICCRE57112.2023.10155585","DOIUrl":"https://doi.org/10.1109/ICCRE57112.2023.10155585","url":null,"abstract":"A novel deep learning-based visual servoing architecture “DLVS” is proposed for control of an unmanned aerial vehicle (UAV) capable of quasi-stationary flight with a camera mounted under the vehicle to track a target consisting of a finite set of stationary points lying in a plane. Current Deep Learning and Reinforcement Learning (RL) based end-to-end servoing approaches rely on training convolutional neural networks using color images with known camera poses to learn the visual features in the environment suitable for servoing tasks. This approach limits the application of the network to available environments where the dataset was collected. Moreover, we cannot deploy such networks on the low-power computers present onboard the UAV. The proposed solution employs a time series architecture to learn temporal data from sequential values to output the control cues to the flight controller. The low computational complexity and flexibility of the DLVS architecture ensure real-time onboard tracking for virtually any target. The algorithm was thoroughly validated in real-life environments and outperformed the current state-of-the-art in terms of time efficiency and accuracy.","PeriodicalId":285164,"journal":{"name":"2023 8th International Conference on Control and Robotics Engineering (ICCRE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129523775","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Better Multi-step Time Series Prediction Using Sparse and Deep Echo State Network","authors":"Kristsana Seepanomwan","doi":"10.1109/ICCRE57112.2023.10155604","DOIUrl":"https://doi.org/10.1109/ICCRE57112.2023.10155604","url":null,"abstract":"Multi-step time series prediction is essential in real-world applications but challenging to obtain accurately due to a fallacy accumulation. Incrementing the required future steps typically results in performance degradation. Data-driven machine learning techniques have the potential to tackle this task but demand significant or special computing powers such as memory and graphics processing units (GPUs). This work demonstrates that Deep Echo State Network (DeepESN) with a sparse configuration can capture multi-step prediction in a comparable or even better performance while demanding lower resources and processing times. Most experimental results documented in the literature examine only one or a few multi-step ahead. Here we report the prediction of up to 250 future steps with better correlation-of-coefficient contrasting to the baseline models. Sparsing the projection of the input signal to each reservoir of the DeepESN can reduce the circumstances of overfitting in time series learning. This finding could lead to utilizing deep learning models with affordable resources and processing times.","PeriodicalId":285164,"journal":{"name":"2023 8th International Conference on Control and Robotics Engineering (ICCRE)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117257788","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}
Abelardo José Banegas Dubón, Alexandro Jaffet Cribas Ramos, J. L. Ordoñez-Ávila
{"title":"Design and Fabrication of a Quadruped Zoomorphic Robot and Its Mathematical Model Using Denavit-Hartenberg Algorithm","authors":"Abelardo José Banegas Dubón, Alexandro Jaffet Cribas Ramos, J. L. Ordoñez-Ávila","doi":"10.1109/ICCRE57112.2023.10155594","DOIUrl":"https://doi.org/10.1109/ICCRE57112.2023.10155594","url":null,"abstract":"Thanks to advances in technology, robotics has been able to effectively replace human beings in dangerous situations and tasks such as exploration, search and rescue and cleaning of hazardous environments. One of the types of robots use to replace human beings in these situations are zoomorphic robots. Therefore, this investigation has the objective of designing and fabricating a quadruped zoomorphic robot with 8 DOF that allows remote control and monitoring through an IOT interface and a mathematical model that describes its kinematics. For the design of this robot, the Hierarchical methodology is proposed, which allows the description of the different disciplines involve in the design. The concept was designed and tested in SolidWorks Motion and Simulation. As a main result, equations are developed to correct the position of the center of mass and prevent the robot from losing balance. It was concluded that the movement pattern that offers the most stability to a quadruped robot is moving one limb at a time in a diagonally-crossed manner.","PeriodicalId":285164,"journal":{"name":"2023 8th International Conference on Control and Robotics Engineering (ICCRE)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128406332","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}
Yutaro Yamada, Jacinto Colan, Ana Davila, Y. Hasegawa
{"title":"Task Segmentation Based on Transition State Clustering for Surgical Robot Assistance","authors":"Yutaro Yamada, Jacinto Colan, Ana Davila, Y. Hasegawa","doi":"10.1109/ICCRE57112.2023.10155581","DOIUrl":"https://doi.org/10.1109/ICCRE57112.2023.10155581","url":null,"abstract":"Understanding surgical tasks represents an important challenge for autonomy in surgical robotic systems. To achieve this, we propose an online task segmentation framework that uses hierarchical transition state clustering to activate predefined robot assistance. Our approach involves performing a first clustering on visual features and a subsequent clustering on robot kinematic features for each visual cluster. This enables to capture relevant task transition information on each modality independently. The approach is implemented for a pick-and-place task commonly found in surgical training. The validation of the transition segmentation showed high accuracy and fast computation time. We have integrated the transition recognition module with predefined robot-assisted tool positioning. The complete framework has shown benefits in reducing task completion time and cognitive workload.","PeriodicalId":285164,"journal":{"name":"2023 8th International Conference on Control and Robotics Engineering (ICCRE)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127144718","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}
Jakrin Butdee, W. Kongprawechnon, Hiroki Nakahara, N. Chayopitak, Cherdsak Kingkan, R. Pupadubsin
{"title":"Pattern Recognition of Partial Discharge Faults Using Convolutional Neural Network (CNN)","authors":"Jakrin Butdee, W. Kongprawechnon, Hiroki Nakahara, N. Chayopitak, Cherdsak Kingkan, R. Pupadubsin","doi":"10.1109/ICCRE57112.2023.10155616","DOIUrl":"https://doi.org/10.1109/ICCRE57112.2023.10155616","url":null,"abstract":"Partial Discharge (PD) analysis is one the most widely used methods to monitor and determine the fault conditions of electrical equipment, especially in high-voltage environments such as power transformers and power generators. Conventional method of PD analysis that is widely used in multiple studies and commercial equipment usually rely on a feature extraction technique such as the Phase Resolved Partial Discharge (PRPD) Pattern to assist PD experts to inspect the faults in the system. This study proposes a CNN based method to recognize the PRPD patterns for different types of PD. The differences of each type of PD, data pre-processing steps and visualization of PD waveforms in PRPD patterns are discussed in details. The obtained PRPD pattern images are then used to train a pattern recognition model and the results show that the proposed method can effectively classify different types of PD under consideration.","PeriodicalId":285164,"journal":{"name":"2023 8th International Conference on Control and Robotics Engineering (ICCRE)","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126620384","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}