Pub Date : 2017-06-20DOI: 10.1109/ICIEA.2017.8283155
A. Perera, Ravindra Ranasinghe, G. Dissanayake
Place recognition in a crowded and cluttered environment is a challenging task due to its dynamic characteristics such as moving obstacles, varying lighting conditions and occlusions. This work presents a robust place recognition technique that could be applied into a similar environment, by combining well known Bag of Words technique with a feedforward neural network. The feedforward neural network we use have three layers with a single hidden layer and it relies on rectifier and softmax activation functions. We employ cross entropy function to model the cost of our neural network and utilize Adam algorithm for minimizing this cost at the training phase. The output layer with softmax activation in the neural network, produces a vector of probabilities which represent the likelihood of test image being captured from a given region. These values are further improved by incorporating a transition matrix which is based on the building layout. We have evaluated our neural network based place recognition technique with data collected from a crowded indoor shopping mall and promising results have been observed by this approach. We also have analyzed the behavior of neural network for changes in hyper-parameters and presented the results.
{"title":"A neural network based place recognition technique for a crowded indoor environment","authors":"A. Perera, Ravindra Ranasinghe, G. Dissanayake","doi":"10.1109/ICIEA.2017.8283155","DOIUrl":"https://doi.org/10.1109/ICIEA.2017.8283155","url":null,"abstract":"Place recognition in a crowded and cluttered environment is a challenging task due to its dynamic characteristics such as moving obstacles, varying lighting conditions and occlusions. This work presents a robust place recognition technique that could be applied into a similar environment, by combining well known Bag of Words technique with a feedforward neural network. The feedforward neural network we use have three layers with a single hidden layer and it relies on rectifier and softmax activation functions. We employ cross entropy function to model the cost of our neural network and utilize Adam algorithm for minimizing this cost at the training phase. The output layer with softmax activation in the neural network, produces a vector of probabilities which represent the likelihood of test image being captured from a given region. These values are further improved by incorporating a transition matrix which is based on the building layout. We have evaluated our neural network based place recognition technique with data collected from a crowded indoor shopping mall and promising results have been observed by this approach. We also have analyzed the behavior of neural network for changes in hyper-parameters and presented the results.","PeriodicalId":443463,"journal":{"name":"2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131984615","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 : 2017-06-20DOI: 10.1109/ICIEA.2017.8283134
Miao Zhang, Huiqi Li, S. Su
This paper presents an evolutionary approach which treats the image segmentation as a graph partitioning problem. An image is described as a weighted undirected graph where pixels correspond to nodes, and those pixels with similar values and positions are connected by edges. The weighted normalized cut criterion (WNcut) is used in this paper for this graph partitioning problem to measures both the dissimilarity between different partitions and the total similarity within the groups. This paper adopts a 2-dimensional representation of chromosome to directly present an image segmentation which is beneficial both to the genetic operators in the evolutionary process and to efficiently reduce the running time. In addition, the proposed evolutionary algorithm uses prior user's preference information to control the segments of the image through a random walker approach to initialize population. Experimental results demonstrate that our proposed algorithm is able to efficiently handle segmentation cases that segments images into several partitions based on human visual perception. The statistical results of entropy-based evaluation also suggest that our approach could achieve a more accurate segmentation.
{"title":"An evolutionary algorithm with 2-D encoding for image segmentation","authors":"Miao Zhang, Huiqi Li, S. Su","doi":"10.1109/ICIEA.2017.8283134","DOIUrl":"https://doi.org/10.1109/ICIEA.2017.8283134","url":null,"abstract":"This paper presents an evolutionary approach which treats the image segmentation as a graph partitioning problem. An image is described as a weighted undirected graph where pixels correspond to nodes, and those pixels with similar values and positions are connected by edges. The weighted normalized cut criterion (WNcut) is used in this paper for this graph partitioning problem to measures both the dissimilarity between different partitions and the total similarity within the groups. This paper adopts a 2-dimensional representation of chromosome to directly present an image segmentation which is beneficial both to the genetic operators in the evolutionary process and to efficiently reduce the running time. In addition, the proposed evolutionary algorithm uses prior user's preference information to control the segments of the image through a random walker approach to initialize population. Experimental results demonstrate that our proposed algorithm is able to efficiently handle segmentation cases that segments images into several partitions based on human visual perception. The statistical results of entropy-based evaluation also suggest that our approach could achieve a more accurate segmentation.","PeriodicalId":443463,"journal":{"name":"2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126459931","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 : 2017-06-18DOI: 10.1109/ICIEA.2017.8282911
T. G. Arora, M. Renge, M. Aware
High-frequency components and large amplitudes of the common mode voltage (CMV) at the motor neutral point generate high-frequency common mode current (CMC) to the ground path and induce voltage on the shaft, which eventually reduces the machine life. This paper presents the effect of switching frequency and motor speed on CMV, CMC and shaft voltage. Three parameters viz. common mode voltage peak factor, common mode current peak factor and shaft voltage peak factor are proposed to define the stresses generated at ground wall insulation and bearings when induction motor is operated with inverter. The results can be used for verifying the feasibility of the mitigation techniques for CMV and bearing currents at different switching frequencies and motor speed.
{"title":"Effects of switching frequency and motor speed on common mode voltage, common mode current and shaft voltage in PWM inverter-fed induction motors","authors":"T. G. Arora, M. Renge, M. Aware","doi":"10.1109/ICIEA.2017.8282911","DOIUrl":"https://doi.org/10.1109/ICIEA.2017.8282911","url":null,"abstract":"High-frequency components and large amplitudes of the common mode voltage (CMV) at the motor neutral point generate high-frequency common mode current (CMC) to the ground path and induce voltage on the shaft, which eventually reduces the machine life. This paper presents the effect of switching frequency and motor speed on CMV, CMC and shaft voltage. Three parameters viz. common mode voltage peak factor, common mode current peak factor and shaft voltage peak factor are proposed to define the stresses generated at ground wall insulation and bearings when induction motor is operated with inverter. The results can be used for verifying the feasibility of the mitigation techniques for CMV and bearing currents at different switching frequencies and motor speed.","PeriodicalId":443463,"journal":{"name":"2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA)","volume":"174 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124272070","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 : 2017-06-18DOI: 10.1109/ICIEA.2017.8282968
J. Barbosa, P. Leitão
The Cyber-Physical System (CPS) paradigm promotes the decentralization and distribution of the logic control as well as the integration of cyber and physical counterparts. In parallel, self-organization allows the dynamic and automatic system re-configuration responding to condition and environment changes. Modeling and simulation assume a crucial importance in the design of such complex, distributed, and self-organized systems, in the way that the detected and debugged errors may be corrected before the deployment into the real system, as well different strategies can be tested and evaluated. Agent-based modeling tools are computational frameworks able to analyze, experiment and compare systems populated by cooperative agents, supporting the fast prototyping of agent-based solutions exhibiting self-∗ properties. In this paper, the NetLogo tool was used to model and simulate the agent-based control layer of a small scale CPS, which control uses self-organization principles.
{"title":"Agent-based modeling and simulation of a small scale cyber-physical system using NetLogo","authors":"J. Barbosa, P. Leitão","doi":"10.1109/ICIEA.2017.8282968","DOIUrl":"https://doi.org/10.1109/ICIEA.2017.8282968","url":null,"abstract":"The Cyber-Physical System (CPS) paradigm promotes the decentralization and distribution of the logic control as well as the integration of cyber and physical counterparts. In parallel, self-organization allows the dynamic and automatic system re-configuration responding to condition and environment changes. Modeling and simulation assume a crucial importance in the design of such complex, distributed, and self-organized systems, in the way that the detected and debugged errors may be corrected before the deployment into the real system, as well different strategies can be tested and evaluated. Agent-based modeling tools are computational frameworks able to analyze, experiment and compare systems populated by cooperative agents, supporting the fast prototyping of agent-based solutions exhibiting self-∗ properties. In this paper, the NetLogo tool was used to model and simulate the agent-based control layer of a small scale CPS, which control uses self-organization principles.","PeriodicalId":443463,"journal":{"name":"2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121251996","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 : 2017-06-18DOI: 10.1109/ICIEA.2017.8283126
Jinxin Cheng, Jiang Chen, Hang Xiang
Construct optimization platform. Adopt artificial neural network approximate model with global and local combinatorial optimization method. Then optimize the rotor of transonic axial flow compressor Stage35 in stage circumstance. The optimization variables are axial movement distance, circumference movement distance and the stagger angle of the hub, middle and tip section. With control of the mass flow and the pressure ratio, maximum efficiency is set as the optimization goal, the result is reached as the margin remains unchanged and the adiabatic efficiency increases by 0.3% over the whole range of incidence conditions at the designed rotation speed.
{"title":"Optimization of rotor blade in stage circumstance for transonic axial flow compressor","authors":"Jinxin Cheng, Jiang Chen, Hang Xiang","doi":"10.1109/ICIEA.2017.8283126","DOIUrl":"https://doi.org/10.1109/ICIEA.2017.8283126","url":null,"abstract":"Construct optimization platform. Adopt artificial neural network approximate model with global and local combinatorial optimization method. Then optimize the rotor of transonic axial flow compressor Stage35 in stage circumstance. The optimization variables are axial movement distance, circumference movement distance and the stagger angle of the hub, middle and tip section. With control of the mass flow and the pressure ratio, maximum efficiency is set as the optimization goal, the result is reached as the margin remains unchanged and the adiabatic efficiency increases by 0.3% over the whole range of incidence conditions at the designed rotation speed.","PeriodicalId":443463,"journal":{"name":"2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125477881","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 proposes a new multifractal analysis based feature representation for object representation. Multiple Fractal Dimensions (MFD) are calculated to describe the distribution of fractal dimensions measured on a finite number of point sets extracted from the image. The proposed MFD feature is theoretically proven to be invariant to articulations, which is a desirable characteristic for faces and pedestrian due to the existence of expressions, posture and illumination variations. The new object representation is extensively evaluated on pedestrian detection problem. The experiments INRIA pedestrian databases show that our method achieves a much better performance than baseline methods in terms of recognition rates.
{"title":"Pedestrian detection based on multifractal analysis","authors":"Baochang Zhang, Hainan Wang, Hong Zheng, Ya-wei Hou, Chenglong He, Baoguo Yu","doi":"10.1109/ICIEA.2017.8282820","DOIUrl":"https://doi.org/10.1109/ICIEA.2017.8282820","url":null,"abstract":"This paper proposes a new multifractal analysis based feature representation for object representation. Multiple Fractal Dimensions (MFD) are calculated to describe the distribution of fractal dimensions measured on a finite number of point sets extracted from the image. The proposed MFD feature is theoretically proven to be invariant to articulations, which is a desirable characteristic for faces and pedestrian due to the existence of expressions, posture and illumination variations. The new object representation is extensively evaluated on pedestrian detection problem. The experiments INRIA pedestrian databases show that our method achieves a much better performance than baseline methods in terms of recognition rates.","PeriodicalId":443463,"journal":{"name":"2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124579970","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 : 2017-06-18DOI: 10.1109/ICIEA.2017.8283120
Jun Wang, Shoudong Huang, Liang Zhao, J. Ge, S. He, Chengqi Zhang, Xiangyu Wang
High-quality 3D reconstruction of large-scale indoor scene is the key to combine Simultaneous Localization And Mapping (SLAM) with other applications, such as building inspection and construction monitoring. However, the requirement of global consistency brings challenges to both localization and mapping. In particular, significant localization and mapping error can happen when standard SLAM techniques are used when dealing with the area of featureless walls and roofs. This paper proposed a novel framework aiming to reconstruct a high-quality, globally consistent 3D model for indoor environments using only a RGB-D sensor. We first introduce the sparse and dense feature constraints in the local bundle adjustment. Then, the planar constraints are incorporated in the global bundle adjustment. We fuse the point clouds in a truncated signed distance function volume, from which the high quality mesh can be extracted. Our framework leads to a comprehensive 3D scanning solution for indoor scene, enabling high-quality results and potential applications in building information system. The video of 3D models reconstructed by the method proposed in this paper is available at https://youtu.be/DWMP4YfeNeY.
{"title":"High quality 3D reconstruction of indoor environments using RGB-D sensors","authors":"Jun Wang, Shoudong Huang, Liang Zhao, J. Ge, S. He, Chengqi Zhang, Xiangyu Wang","doi":"10.1109/ICIEA.2017.8283120","DOIUrl":"https://doi.org/10.1109/ICIEA.2017.8283120","url":null,"abstract":"High-quality 3D reconstruction of large-scale indoor scene is the key to combine Simultaneous Localization And Mapping (SLAM) with other applications, such as building inspection and construction monitoring. However, the requirement of global consistency brings challenges to both localization and mapping. In particular, significant localization and mapping error can happen when standard SLAM techniques are used when dealing with the area of featureless walls and roofs. This paper proposed a novel framework aiming to reconstruct a high-quality, globally consistent 3D model for indoor environments using only a RGB-D sensor. We first introduce the sparse and dense feature constraints in the local bundle adjustment. Then, the planar constraints are incorporated in the global bundle adjustment. We fuse the point clouds in a truncated signed distance function volume, from which the high quality mesh can be extracted. Our framework leads to a comprehensive 3D scanning solution for indoor scene, enabling high-quality results and potential applications in building information system. The video of 3D models reconstructed by the method proposed in this paper is available at https://youtu.be/DWMP4YfeNeY.","PeriodicalId":443463,"journal":{"name":"2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132562838","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 : 2017-06-18DOI: 10.1109/ICIEA.2017.8282808
Qin Haihong, Ma Ceyu, Wang Dan, Xie Haotian, Zhu Ziyue, Xuan Kefeng, Wang Shi-shan
Silicon Carbide (SiC) Metal-Oxide-Semiconductor Field-Effect Transistors (MOSFETs) have started gaining significant importance in various application areas of power electronics. During the last decade, SiC MOSFETs count not only as potential, but more importantly as alternative to silicon counterparts for high efficiency, high switching frequencies and high temperatures applications. Various SiC MOSFET driver designs have been proposed and their advantages and disadvantages are discussed as well. However, the design of gate drivers for SiC MOSFETs is very challenging. In particular, a sophisticated driver design is not only associated with properly switching the MOSFETs and decreasing the switching power losses, but also it must comply with the electromagnetic compatibility. This paper shows an overview of gate drivers for SiC MOSFETs. In particular, the basic operating principle of each driver along with their applicability and drawbacks are presented.
{"title":"An overview of SiC MOSFET gate drivers","authors":"Qin Haihong, Ma Ceyu, Wang Dan, Xie Haotian, Zhu Ziyue, Xuan Kefeng, Wang Shi-shan","doi":"10.1109/ICIEA.2017.8282808","DOIUrl":"https://doi.org/10.1109/ICIEA.2017.8282808","url":null,"abstract":"Silicon Carbide (SiC) Metal-Oxide-Semiconductor Field-Effect Transistors (MOSFETs) have started gaining significant importance in various application areas of power electronics. During the last decade, SiC MOSFETs count not only as potential, but more importantly as alternative to silicon counterparts for high efficiency, high switching frequencies and high temperatures applications. Various SiC MOSFET driver designs have been proposed and their advantages and disadvantages are discussed as well. However, the design of gate drivers for SiC MOSFETs is very challenging. In particular, a sophisticated driver design is not only associated with properly switching the MOSFETs and decreasing the switching power losses, but also it must comply with the electromagnetic compatibility. This paper shows an overview of gate drivers for SiC MOSFETs. In particular, the basic operating principle of each driver along with their applicability and drawbacks are presented.","PeriodicalId":443463,"journal":{"name":"2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134008143","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 : 2017-06-18DOI: 10.1109/ICIEA.2017.8283153
K. Thiyagarajan, S. Kodagoda, Linh Van Nguyen
Sensors play a vital role in monitoring the important parameters of critical infrastructure. Failure of such sensors causes destabilization to the entire system. In this regard, this paper proposes a predictive analytics solution for detecting the failure of a sensor that measures surface temperature from an urban sewer. The proposed approach incorporates a forecasting technique based on the past time series of sparse data using an autoregressive integrated moving average (ARIMA) model. Based on the 95% forecast interval and continuity of faulty data, a criterion was set to detect anomalies and to issue a warning for sensor failure. The forecasted and faulty data were assumed Gaussian distributed. By using the probability density of the distribution, the mean and variance were computed for faulty data to examine the abnormality in the variance value of each day to detect the sensor failure. The experimental results on the sewer temperature data are appealing.
{"title":"Predictive analytics for detecting sensor failure using autoregressive integrated moving average model","authors":"K. Thiyagarajan, S. Kodagoda, Linh Van Nguyen","doi":"10.1109/ICIEA.2017.8283153","DOIUrl":"https://doi.org/10.1109/ICIEA.2017.8283153","url":null,"abstract":"Sensors play a vital role in monitoring the important parameters of critical infrastructure. Failure of such sensors causes destabilization to the entire system. In this regard, this paper proposes a predictive analytics solution for detecting the failure of a sensor that measures surface temperature from an urban sewer. The proposed approach incorporates a forecasting technique based on the past time series of sparse data using an autoregressive integrated moving average (ARIMA) model. Based on the 95% forecast interval and continuity of faulty data, a criterion was set to detect anomalies and to issue a warning for sensor failure. The forecasted and faulty data were assumed Gaussian distributed. By using the probability density of the distribution, the mean and variance were computed for faulty data to examine the abnormality in the variance value of each day to detect the sensor failure. The experimental results on the sewer temperature data are appealing.","PeriodicalId":443463,"journal":{"name":"2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115699887","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 : 2017-06-18DOI: 10.1109/ICIEA.2017.8283046
Li Li, Jie Wu, Yixiang Xu, Jun Che, Jin Liang
Unmanned Aerial Vehicles (UAVs) are widely used in civil and military fields. For a working UAV, the energy is limited, the coverage distance is short and the loading capacity is restricted. In order to execute more tasks in complex environment, there is a trend that UAVs are used in cluster and coordinated with each other. Wireless charging technology can charge the unmanned aerial vehicles in time and effectively extend the life of UAVs to reduce the number of disabled UAVs. In this paper, the scheduling algorithm for charging UAVs cluster is studied. By comparing with other optimization algorithms, the most suitable charge scheduling control algorithm can be evaluated according to the number of surviving nodes in a certain time in the rechargeable unmanned aircraft group.
{"title":"Energy-controlled optimization algorithm for rechargeable unmanned aerial vehicle network","authors":"Li Li, Jie Wu, Yixiang Xu, Jun Che, Jin Liang","doi":"10.1109/ICIEA.2017.8283046","DOIUrl":"https://doi.org/10.1109/ICIEA.2017.8283046","url":null,"abstract":"Unmanned Aerial Vehicles (UAVs) are widely used in civil and military fields. For a working UAV, the energy is limited, the coverage distance is short and the loading capacity is restricted. In order to execute more tasks in complex environment, there is a trend that UAVs are used in cluster and coordinated with each other. Wireless charging technology can charge the unmanned aerial vehicles in time and effectively extend the life of UAVs to reduce the number of disabled UAVs. In this paper, the scheduling algorithm for charging UAVs cluster is studied. By comparing with other optimization algorithms, the most suitable charge scheduling control algorithm can be evaluated according to the number of surviving nodes in a certain time in the rechargeable unmanned aircraft group.","PeriodicalId":443463,"journal":{"name":"2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115922703","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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