Pub Date : 2020-09-01DOI: 10.1109/CACRE50138.2020.9230079
Bo Li, Jue Wang, Nan Xia
Aiming at the important research topic of optimal scheduling in microgrid field, the model for multi-objective optimal dispatching of microgrid is established with the objective of minimum economic and environmental treatment costs. On this basis, the model is organically integrated with constraint handling technology, multi-objective optimization and biogeography-based optimization algorithm and then a constrained multi-objective evolutionary model for biogeography-based optimization is further established. The corresponding constraint handling mechanism, the determining strategy of habitat suitability index and migration strategy are improved, and the convergence performance and the distribution uniformity of Pareto frontier for multi-objective evolutionary algorithm are effectively enhanced. Applied to the optimal scheduling of typical microgrid systems, the effectiveness of the proposed model and method is verified.
{"title":"Dynamic Optimal Scheduling of Microgrid Based on ε constraint multi-objective Biogeography-based Optimization Algorithm","authors":"Bo Li, Jue Wang, Nan Xia","doi":"10.1109/CACRE50138.2020.9230079","DOIUrl":"https://doi.org/10.1109/CACRE50138.2020.9230079","url":null,"abstract":"Aiming at the important research topic of optimal scheduling in microgrid field, the model for multi-objective optimal dispatching of microgrid is established with the objective of minimum economic and environmental treatment costs. On this basis, the model is organically integrated with constraint handling technology, multi-objective optimization and biogeography-based optimization algorithm and then a constrained multi-objective evolutionary model for biogeography-based optimization is further established. The corresponding constraint handling mechanism, the determining strategy of habitat suitability index and migration strategy are improved, and the convergence performance and the distribution uniformity of Pareto frontier for multi-objective evolutionary algorithm are effectively enhanced. Applied to the optimal scheduling of typical microgrid systems, the effectiveness of the proposed model and method is verified.","PeriodicalId":325195,"journal":{"name":"2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114526612","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 : 2020-09-01DOI: 10.1109/CACRE50138.2020.9229997
Xiao Li, Dan Wang, Yancheng Liu, Zhouhua Peng
This paper presents a new approach to fuse information in special form. To determine the position and heading of mobile robot, the information from fixation vision geometric constraint must be exploited. However, geometric constraint is not measurement data from sensor, cannot be fused directly. Therefore the concept of “soft sensor” is adopted. Its application to mobile robot localization is shown with simulation in this paper.
{"title":"Mobile Robot Localization Using Soft Sensor","authors":"Xiao Li, Dan Wang, Yancheng Liu, Zhouhua Peng","doi":"10.1109/CACRE50138.2020.9229997","DOIUrl":"https://doi.org/10.1109/CACRE50138.2020.9229997","url":null,"abstract":"This paper presents a new approach to fuse information in special form. To determine the position and heading of mobile robot, the information from fixation vision geometric constraint must be exploited. However, geometric constraint is not measurement data from sensor, cannot be fused directly. Therefore the concept of “soft sensor” is adopted. Its application to mobile robot localization is shown with simulation in this paper.","PeriodicalId":325195,"journal":{"name":"2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134359175","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 : 2020-09-01DOI: 10.1109/CACRE50138.2020.9230243
Mingzhu Li, Xi Feng
Due to the hysteresis and non-linearity of constant pressure water supply control system, it is difficult to realize accurate control of water supply pressure. To address this problem, an IABC-PID control algorithm based on improved artificial bee colony algorithm is proposed in this paper. To address the shortcomings of the basic artificial bee colony algorithm, which converges slowly and is prone to local optimality, a full dimensional learning strategy is introduced in the neighborhood search of the employed foragers. At the same time, Gaussian variation and chaotic perturbations are introduced to enhance the local search capability and increase the population diversity, thus speeding up the convergence speed and improving the search accuracy. The simulation results show that the IABC- PID control algorithm outperforms the ABC-PID method in terms of convergence speed, search accuracy and operational stability. Compared with the response curve method, the IABC-PID algorithm has no overshoot, small adjustment time, better dynamic performance, steady-state performance and robustness. The algorithm provides a theoretical basis for real-time online PID parameter rectification of constant pressure water supply system and provides an effective means for energy saving and consumption reduction of pumps.
{"title":"Application of Improved Artificial Bee Colony Algorithm in constant pressure water supply system","authors":"Mingzhu Li, Xi Feng","doi":"10.1109/CACRE50138.2020.9230243","DOIUrl":"https://doi.org/10.1109/CACRE50138.2020.9230243","url":null,"abstract":"Due to the hysteresis and non-linearity of constant pressure water supply control system, it is difficult to realize accurate control of water supply pressure. To address this problem, an IABC-PID control algorithm based on improved artificial bee colony algorithm is proposed in this paper. To address the shortcomings of the basic artificial bee colony algorithm, which converges slowly and is prone to local optimality, a full dimensional learning strategy is introduced in the neighborhood search of the employed foragers. At the same time, Gaussian variation and chaotic perturbations are introduced to enhance the local search capability and increase the population diversity, thus speeding up the convergence speed and improving the search accuracy. The simulation results show that the IABC- PID control algorithm outperforms the ABC-PID method in terms of convergence speed, search accuracy and operational stability. Compared with the response curve method, the IABC-PID algorithm has no overshoot, small adjustment time, better dynamic performance, steady-state performance and robustness. The algorithm provides a theoretical basis for real-time online PID parameter rectification of constant pressure water supply system and provides an effective means for energy saving and consumption reduction of pumps.","PeriodicalId":325195,"journal":{"name":"2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130361508","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}
Electric power transformer is one of the most necessary part in power system, and hence, it’s significant to diagnose the transformer malfunction in advance; A methods of prediction for transformer malfunction based on oil chromatography is described; 4 models for time series prediction are illustrated, and the specific methods for model identification and ordering are explained; The time series model was applied to predict transformer malfunction in the oil chromatography analysis example, and accurate results were obtained, which shows that the method described in this paper can effectively predict the concentration of dissolved gas in transformer oil in future, and diagnose the types of malfunctions so that meet the actual need of projects.
{"title":"A Method of Prediction for Transformer Malfunction Based on Oil Chromatography","authors":"Hao Wu, Yang Zhou, Chuanqi Yang, Hongmei Zhu, Dongxin Hao, Shuangzan Ren","doi":"10.1109/CACRE50138.2020.9230296","DOIUrl":"https://doi.org/10.1109/CACRE50138.2020.9230296","url":null,"abstract":"Electric power transformer is one of the most necessary part in power system, and hence, it’s significant to diagnose the transformer malfunction in advance; A methods of prediction for transformer malfunction based on oil chromatography is described; 4 models for time series prediction are illustrated, and the specific methods for model identification and ordering are explained; The time series model was applied to predict transformer malfunction in the oil chromatography analysis example, and accurate results were obtained, which shows that the method described in this paper can effectively predict the concentration of dissolved gas in transformer oil in future, and diagnose the types of malfunctions so that meet the actual need of projects.","PeriodicalId":325195,"journal":{"name":"2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130362782","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 : 2020-09-01DOI: 10.1109/CACRE50138.2020.9230115
Jingping Shao, Yangyang Chen
A novelty of distributed parameter estimation strategy for a class of nonlinear system with a time-varying parameter is proposed in this paper. The approach relies upon the concepts of invariant manifold and cooperative persistent excitation condition, does not require a priori knowledge of the time-varying parameters. In addition, it is shown that the parameter estimation error is not only bounded but also can converge to a small neighborhood of the origin for sufficiently large value of gain. A numerical simulation example is presented to demonstrate the effectiveness of the proposed method.
{"title":"Distributed Parameter Estimation Using Invariant Manifold Approach","authors":"Jingping Shao, Yangyang Chen","doi":"10.1109/CACRE50138.2020.9230115","DOIUrl":"https://doi.org/10.1109/CACRE50138.2020.9230115","url":null,"abstract":"A novelty of distributed parameter estimation strategy for a class of nonlinear system with a time-varying parameter is proposed in this paper. The approach relies upon the concepts of invariant manifold and cooperative persistent excitation condition, does not require a priori knowledge of the time-varying parameters. In addition, it is shown that the parameter estimation error is not only bounded but also can converge to a small neighborhood of the origin for sufficiently large value of gain. A numerical simulation example is presented to demonstrate the effectiveness of the proposed method.","PeriodicalId":325195,"journal":{"name":"2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133730574","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 : 2020-09-01DOI: 10.1109/CACRE50138.2020.9229989
Fengjie Cao, Xuemei Xu, Peng Ouyang, Yipeng Ding, K. Sun
Electroencephalography (EEG) can be applied in medical diagnosis forecasts via using Brain-Computer Interface (BCI) technology. EEG signals are low voltage signals that are susceptible to various types of noise such as 50 Hz power frequency, noise between the electrodes and the skin and so on. In this work, an enhancement method for EEG data based on a deep neural network (DNN) architecture search method in which the spatial feature loss acts as a regularizer while training the end-to-end network for best noise removal effect is proposed. The proposed system realizes noise reduction by using DNNs, which employs an alternative objective function combining spatial feature loss with time-domain feature loss. The spatial feature can be obtained by Common Spatial Pattern (CSP) algorithm. Experimental results show that auto DNNs with regularization of spatial feature loss can efficiently eliminate the simulated noise in EEG data and makes the mean square error between predicted values and real values as small as 0.06. In addition, the proposed objective function outperforms objective function with single time-domain feature loss. Meanwhile, the number of parameters in auto DNNs is obviously less than other models by 81.7% to 94.2% and also less when using proposed objective function than not use it by 28.6%. These results demonstrate that proposed DNNs based method can reduce parameters and computation. Therefore the proposed method is promising for the wearable application and embedded scenarios.
{"title":"EEG Enhancement by Auto DNNs with Regularization of Spatial Feature Loss","authors":"Fengjie Cao, Xuemei Xu, Peng Ouyang, Yipeng Ding, K. Sun","doi":"10.1109/CACRE50138.2020.9229989","DOIUrl":"https://doi.org/10.1109/CACRE50138.2020.9229989","url":null,"abstract":"Electroencephalography (EEG) can be applied in medical diagnosis forecasts via using Brain-Computer Interface (BCI) technology. EEG signals are low voltage signals that are susceptible to various types of noise such as 50 Hz power frequency, noise between the electrodes and the skin and so on. In this work, an enhancement method for EEG data based on a deep neural network (DNN) architecture search method in which the spatial feature loss acts as a regularizer while training the end-to-end network for best noise removal effect is proposed. The proposed system realizes noise reduction by using DNNs, which employs an alternative objective function combining spatial feature loss with time-domain feature loss. The spatial feature can be obtained by Common Spatial Pattern (CSP) algorithm. Experimental results show that auto DNNs with regularization of spatial feature loss can efficiently eliminate the simulated noise in EEG data and makes the mean square error between predicted values and real values as small as 0.06. In addition, the proposed objective function outperforms objective function with single time-domain feature loss. Meanwhile, the number of parameters in auto DNNs is obviously less than other models by 81.7% to 94.2% and also less when using proposed objective function than not use it by 28.6%. These results demonstrate that proposed DNNs based method can reduce parameters and computation. Therefore the proposed method is promising for the wearable application and embedded scenarios.","PeriodicalId":325195,"journal":{"name":"2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123641568","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 : 2020-09-01DOI: 10.1109/CACRE50138.2020.9230311
Xiangxu Lin, Saifuddin Mahmud, S. Román, Alfred Shaker, Zachary Law, MinYi Lin, Jong-Hoon Kim
Increasing occurrences of natural and man-made disasters have driven the demand for search and rescue (S&R) robots. However, state-of-the-art S&R robots serve as specialpurpose machines with limited use cases. This is in part due to a lack of human-centered designs, particularly in multilateral control and human-robot interactions. Thus, we propose TeleBot-R2, a novel transformable centaur-robot. This robot extends our work presented at the 2018 World Robot Summit, a hybrid humanoid (immersive telepresence) robot with a multilateral control system. Our new version introduces a dual flipper caterpillar track base with an enhanced mechanically dynamic humanoid upper body. This transformer robot can contract into multiple configurations that change it’s support polygon and means of locomotion - allowing it to navigate more efficiently through different terrains. Operational awareness is heightened through a VR immersive control interface that interacts with an AI-assisted multilateral control system. This paper presents our mechanical design, control architecture, immersive interfaces, and AI-assistant.
{"title":"Design of A Novel Transformable Centaur Robot with Multilateral Control Interface for Search and Rescue Missions","authors":"Xiangxu Lin, Saifuddin Mahmud, S. Román, Alfred Shaker, Zachary Law, MinYi Lin, Jong-Hoon Kim","doi":"10.1109/CACRE50138.2020.9230311","DOIUrl":"https://doi.org/10.1109/CACRE50138.2020.9230311","url":null,"abstract":"Increasing occurrences of natural and man-made disasters have driven the demand for search and rescue (S&R) robots. However, state-of-the-art S&R robots serve as specialpurpose machines with limited use cases. This is in part due to a lack of human-centered designs, particularly in multilateral control and human-robot interactions. Thus, we propose TeleBot-R2, a novel transformable centaur-robot. This robot extends our work presented at the 2018 World Robot Summit, a hybrid humanoid (immersive telepresence) robot with a multilateral control system. Our new version introduces a dual flipper caterpillar track base with an enhanced mechanically dynamic humanoid upper body. This transformer robot can contract into multiple configurations that change it’s support polygon and means of locomotion - allowing it to navigate more efficiently through different terrains. Operational awareness is heightened through a VR immersive control interface that interacts with an AI-assisted multilateral control system. This paper presents our mechanical design, control architecture, immersive interfaces, and AI-assistant.","PeriodicalId":325195,"journal":{"name":"2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE)","volume":"310 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127492012","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 : 2020-09-01DOI: 10.1109/CACRE50138.2020.9229908
Qi Zou, Dan Zhang, Shuo Zhang, Xueling Luo
A spatial 3 degree-of-freedom parallel mechanism is proposed in this paper. It contains only Pa joint and revolute joints in each kinematic chain. The motion of the moving platform is verified by means of the theory of screw. The simple and intrinsic geometric relations are employed to solve both the inverse and forward positions and fully-decoupled property. Its singularity configurations are found by using the Jacobian matrix. The translational workspace is obtained and verified through considering joints and linkages limitations.
{"title":"Kinematic analysis of a fully-decoupled parallel manipulator with pure translations","authors":"Qi Zou, Dan Zhang, Shuo Zhang, Xueling Luo","doi":"10.1109/CACRE50138.2020.9229908","DOIUrl":"https://doi.org/10.1109/CACRE50138.2020.9229908","url":null,"abstract":"A spatial 3 degree-of-freedom parallel mechanism is proposed in this paper. It contains only Pa joint and revolute joints in each kinematic chain. The motion of the moving platform is verified by means of the theory of screw. The simple and intrinsic geometric relations are employed to solve both the inverse and forward positions and fully-decoupled property. Its singularity configurations are found by using the Jacobian matrix. The translational workspace is obtained and verified through considering joints and linkages limitations.","PeriodicalId":325195,"journal":{"name":"2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE)","volume":"70 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126144702","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 : 2020-09-01DOI: 10.1109/CACRE50138.2020.9230223
Jie Chen, Yifan Hu, Hailin Liu, Bin Lv, Lin Cao, Hui Li
According to the characteristics of ocean observation data, such as massive, heterogeneous, multi-source, multi-class and multi-dimensional, it is difficult to classify and match ocean observation data quickly and accurately with traditional KNN for large-scale integration. A method of ocean observation data matching based on density clipping and weighted KNN (DC-WKNN) is proposed in this paper. Firstly, according to the distribution density of training samples between different classes, the clipping rule is set up. It can cut out representative samples as new training samples, and reduce the calculation amount of traditional KNN algorithm, so that it can improve the efficiency. Then, according to the distribution characteristics of the training samples in the class, the weight assignment model is established. It can allocate the weight for each training sample and decrease the misjudgment of the boundary points far away from the center of the class, and improve the accuracy. A large number of experimental results based on the data set of the seafloor observatory network show that the calculation complexity is reduced by about 20%. And the accuracy of the algorithm is better than that of the traditional KNN and other improved algorithms. It has good performance for big data classification, especially for the classification of ocean observation data characteristics.
{"title":"Research on Matching Method of Ocean Observation Data Based on DC-WKNN Algorithm","authors":"Jie Chen, Yifan Hu, Hailin Liu, Bin Lv, Lin Cao, Hui Li","doi":"10.1109/CACRE50138.2020.9230223","DOIUrl":"https://doi.org/10.1109/CACRE50138.2020.9230223","url":null,"abstract":"According to the characteristics of ocean observation data, such as massive, heterogeneous, multi-source, multi-class and multi-dimensional, it is difficult to classify and match ocean observation data quickly and accurately with traditional KNN for large-scale integration. A method of ocean observation data matching based on density clipping and weighted KNN (DC-WKNN) is proposed in this paper. Firstly, according to the distribution density of training samples between different classes, the clipping rule is set up. It can cut out representative samples as new training samples, and reduce the calculation amount of traditional KNN algorithm, so that it can improve the efficiency. Then, according to the distribution characteristics of the training samples in the class, the weight assignment model is established. It can allocate the weight for each training sample and decrease the misjudgment of the boundary points far away from the center of the class, and improve the accuracy. A large number of experimental results based on the data set of the seafloor observatory network show that the calculation complexity is reduced by about 20%. And the accuracy of the algorithm is better than that of the traditional KNN and other improved algorithms. It has good performance for big data classification, especially for the classification of ocean observation data characteristics.","PeriodicalId":325195,"journal":{"name":"2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126202028","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}
Due to the energy composition of China rich in coal, poor in oil and low in gas, coal will continue to be the main energy source in China for a long time. In order to improve the intelligence level of coal mine and realize the efficient and clean utilization, coal and gangue sorting is the research focus of many experts and scholars. At present, the construction of the intelligent visual coal and gangue separation platform is complex, the algorithm effect is difficult to verify, and the research and development cost is high, which is not conducive to the progress of technology. In this paper, the intelligent visual gangue sorting system is built based on the robot simulator CoppeliaSim, combining the robot virtual simulation technology with intelligent coal gangue separation system. The modeling of the whole system is highly close to the real scene, and is coordinated with the software program, which lays a good foundation for the intelligent coal and gangue separation, provides a new way to solve the problem of system construction, and improves the level of intelligence by using virtual and real methods.
{"title":"Construction of intelligent visual coal and gangue separation system based on CoppeliaSim","authors":"Zhiyuan Sun, Dongjun Li, Linlin Huang, Biao Liu, Ruiqing Jia","doi":"10.1109/CACRE50138.2020.9230077","DOIUrl":"https://doi.org/10.1109/CACRE50138.2020.9230077","url":null,"abstract":"Due to the energy composition of China rich in coal, poor in oil and low in gas, coal will continue to be the main energy source in China for a long time. In order to improve the intelligence level of coal mine and realize the efficient and clean utilization, coal and gangue sorting is the research focus of many experts and scholars. At present, the construction of the intelligent visual coal and gangue separation platform is complex, the algorithm effect is difficult to verify, and the research and development cost is high, which is not conducive to the progress of technology. In this paper, the intelligent visual gangue sorting system is built based on the robot simulator CoppeliaSim, combining the robot virtual simulation technology with intelligent coal gangue separation system. The modeling of the whole system is highly close to the real scene, and is coordinated with the software program, which lays a good foundation for the intelligent coal and gangue separation, provides a new way to solve the problem of system construction, and improves the level of intelligence by using virtual and real methods.","PeriodicalId":325195,"journal":{"name":"2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE)","volume":"107 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115538035","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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