A novel robot navigation algorithm with global path generation capability is presented. Local minimum is a most intractable but is an encountered frequently problem in potential field based robot navigation.Through ap...A novel robot navigation algorithm with global path generation capability is presented. Local minimum is a most intractable but is an encountered frequently problem in potential field based robot navigation.Through appointing appropriately some virtual local targets on the journey, it can be solved effectively. The key concept employed in this algorithm are the rules that govern when and how to appoint these virtual local targets. When the robot finds itself in danger of local minimum, a virtual local target is appointed to replace the global goal temporarily according to the rules. After the virtual target is reached, the robot continues on its journey by heading towards the global goal. The algorithm prevents the robot from running into local minima anymore. Simulation results showed that it is very effective in complex obstacle environments.展开更多
To improve localization accuracy, the spherical microphone arrays are used to capture high-order wavefield in- formation. For the far field sound sources, the array signal model is constructed based on plane wave deco...To improve localization accuracy, the spherical microphone arrays are used to capture high-order wavefield in- formation. For the far field sound sources, the array signal model is constructed based on plane wave decomposition. The spatial spectrum function is calculated by minimum variance distortionless response (MVDR) to scan the three-dimensional space. The peak values of the spectrum function correspond to the directions of multiple sound sources. A diagonal loading method is adopted to solve the ill-conditioned cross spectrum matrix of the received signals. The loading level depends on the alleviation of the ill-condition of the matrix and the accuracy of the inverse calculation. Compared with plane wave decomposition method, our proposed localization algorithm can acquire high spatial resolution and better estimation for multiple sound source directions, especially in low signal to noise ratio (SNR).展开更多
In distributed cloud storage systems, inevitably there exist multiple node failures at the same time. The existing methods of regenerating codes, including minimum storage regenerating(MSR) codes and minimum bandwidth...In distributed cloud storage systems, inevitably there exist multiple node failures at the same time. The existing methods of regenerating codes, including minimum storage regenerating(MSR) codes and minimum bandwidth regenerating(MBR) codes, are mainly to repair one single or several failed nodes, unable to meet the repair need of distributed cloud storage systems. In this paper, we present locally minimum storage regenerating(LMSR) codes to recover multiple failed nodes at the same time. Specifically, the nodes in distributed cloud storage systems are divided into multiple local groups, and in each local group(4, 2) or(5, 3) MSR codes are constructed. Moreover, the grouping method of storage nodes and the repairing process of failed nodes in local groups are studied. Theoretical analysis shows that LMSR codes can achieve the same storage overhead as MSR codes. Furthermore, we verify by means of simulation that, compared with MSR codes, LMSR codes can reduce the repair bandwidth and disk I/O overhead effectively.展开更多
当移动机器人在行进过程中使用传统人工势场法(artificial potential field method, APF)进行路径规划时,通常会陷入局部最优困境,无法顺利到达目标点。为解决这一问题,首先,对APF算法规划路径失败原因进行分析,其次设置情况判断条件,...当移动机器人在行进过程中使用传统人工势场法(artificial potential field method, APF)进行路径规划时,通常会陷入局部最优困境,无法顺利到达目标点。为解决这一问题,首先,对APF算法规划路径失败原因进行分析,其次设置情况判断条件,判断当机器人陷入局部最小值时,通过在合适位置增加临时引导点的方法,引导其跳出局部极小值点;其次,引入分数阶微积分思想方法结合APF算法,提出混合阶次的分数阶梯度下降法进行位置信息迭代,优化算法的收敛速度和收敛精度;最后,用MATLAB软件对该方法进行仿真,实验结果表明提出的方法可以有效解决局部最小值问题,而且在速度、精度上都有明显的提高,且能适应较为复杂的多障碍物环境,验证了改进方法的有效性、正确性。展开更多
The scalability of routing architectures for large networks is one of the biggest challenges that the Internet faces today.Greedy routing,in which each node is assigned a locator used as a distance metric,recently rec...The scalability of routing architectures for large networks is one of the biggest challenges that the Internet faces today.Greedy routing,in which each node is assigned a locator used as a distance metric,recently received increased attention from researchers and is considered as a potential solution for scalable routing.In this paper,LMD—a local minimum driven method is proposed to compute the topology-based locator.To eliminate the negative effect of the " quasi" greedy property—transfer routes longer than the shortest routes,a two-stage routing strategy is introduced,which combines the greedy routing with source routing.The greedy routing path discovered and compressed in the first stage is then used by the following source-routing stage.Through extensive evaluations,based on synthetic topologies as well as on a snapshot of the real Internet AS(autonomous system)topology,it is shown that LMD guarantees 100%delivery rate on large networks with low stretch.展开更多
The back propagation(BP)neural network method is widely used in bathymetry based on multispectral satellite imagery.However,the classical BP neural network method faces a potential problem because it easily falls into...The back propagation(BP)neural network method is widely used in bathymetry based on multispectral satellite imagery.However,the classical BP neural network method faces a potential problem because it easily falls into a local minimum,leading to model training failure.This study confirmed that the local minimum problem of the BP neural network method exists in the bathymetry field and cannot be ignored.Furthermore,to solve the local minimum problem of the BP neural network method,a bathymetry method based on a BP neural network and ensemble learning(BPEL)is proposed.First,the remote sensing imagery and training sample were used as input datasets,and the BP method was used as the base learner to produce multiple water depth inversion results.Then,a new ensemble strategy,namely the minimum outlying degree method,was proposed and used to integrate the water depth inversion results.Finally,an ensemble bathymetric map was acquired.Anda Reef,northeastern Jiuzhang Atoll,and Pingtan coastal zone were selected as test cases to validate the proposed method.Compared with the BP neural network method,the root-mean-square error and the average relative error of the BPEL method can reduce by 0.65–2.84 m and 16%–46%in the three test cases at most.The results showed that the proposed BPEL method could solve the local minimum problem of the BP neural network method and obtain highly robust and accurate bathymetric maps.展开更多
Sichuan Province,East Western of China,within the area of east longitude 97°21′-108°31′,north latitude 26°03′-34°19′,which is on the Mediterranean seismic zone;with its complicated geological b...Sichuan Province,East Western of China,within the area of east longitude 97°21′-108°31′,north latitude 26°03′-34°19′,which is on the Mediterranean seismic zone;with its complicated geological background,several strong shocks occurred in this district since ancient times.Earthquake catalogue of this area could date back to B.C.26,however,limited by the conditions—technology or funds,lots of minor earthquake have been lost,which could be展开更多
文摘A novel robot navigation algorithm with global path generation capability is presented. Local minimum is a most intractable but is an encountered frequently problem in potential field based robot navigation.Through appointing appropriately some virtual local targets on the journey, it can be solved effectively. The key concept employed in this algorithm are the rules that govern when and how to appoint these virtual local targets. When the robot finds itself in danger of local minimum, a virtual local target is appointed to replace the global goal temporarily according to the rules. After the virtual target is reached, the robot continues on its journey by heading towards the global goal. The algorithm prevents the robot from running into local minima anymore. Simulation results showed that it is very effective in complex obstacle environments.
基金Project supported by the National Natural Science Foundation of China (Grant No.61001160)the Doctoral Foundation of Ministry of Education (Grant No.20093108120018)the Shanghai Leading Academic Discipline Project (Grant No.S30108)
文摘To improve localization accuracy, the spherical microphone arrays are used to capture high-order wavefield in- formation. For the far field sound sources, the array signal model is constructed based on plane wave decomposition. The spatial spectrum function is calculated by minimum variance distortionless response (MVDR) to scan the three-dimensional space. The peak values of the spectrum function correspond to the directions of multiple sound sources. A diagonal loading method is adopted to solve the ill-conditioned cross spectrum matrix of the received signals. The loading level depends on the alleviation of the ill-condition of the matrix and the accuracy of the inverse calculation. Compared with plane wave decomposition method, our proposed localization algorithm can acquire high spatial resolution and better estimation for multiple sound source directions, especially in low signal to noise ratio (SNR).
基金supported in part by the National Natural Science Foundation of China (61640006, 61572188)the Natural Science Foundation of Shaanxi Province, China (2015JM6307, 2016JQ6011)the project of science and technology of Xi’an City (2017088CG/RC051(CADX002))
文摘In distributed cloud storage systems, inevitably there exist multiple node failures at the same time. The existing methods of regenerating codes, including minimum storage regenerating(MSR) codes and minimum bandwidth regenerating(MBR) codes, are mainly to repair one single or several failed nodes, unable to meet the repair need of distributed cloud storage systems. In this paper, we present locally minimum storage regenerating(LMSR) codes to recover multiple failed nodes at the same time. Specifically, the nodes in distributed cloud storage systems are divided into multiple local groups, and in each local group(4, 2) or(5, 3) MSR codes are constructed. Moreover, the grouping method of storage nodes and the repairing process of failed nodes in local groups are studied. Theoretical analysis shows that LMSR codes can achieve the same storage overhead as MSR codes. Furthermore, we verify by means of simulation that, compared with MSR codes, LMSR codes can reduce the repair bandwidth and disk I/O overhead effectively.
文摘当移动机器人在行进过程中使用传统人工势场法(artificial potential field method, APF)进行路径规划时,通常会陷入局部最优困境,无法顺利到达目标点。为解决这一问题,首先,对APF算法规划路径失败原因进行分析,其次设置情况判断条件,判断当机器人陷入局部最小值时,通过在合适位置增加临时引导点的方法,引导其跳出局部极小值点;其次,引入分数阶微积分思想方法结合APF算法,提出混合阶次的分数阶梯度下降法进行位置信息迭代,优化算法的收敛速度和收敛精度;最后,用MATLAB软件对该方法进行仿真,实验结果表明提出的方法可以有效解决局部最小值问题,而且在速度、精度上都有明显的提高,且能适应较为复杂的多障碍物环境,验证了改进方法的有效性、正确性。
文摘针对基于机器视觉的小型机械零件识别速度慢、定位不精确等问题,文章提出一种改进UNet(improve U-Net,IU-Net)和最小外接矩阵(minimum bounding rectangle,MBR)结合的小型机械零件识别和定位方法(IU-Net-MBR)。首先,搭建视觉分拣试验平台,制作小型机械零件数据集;其次,为了提高特征提取效率,将U-Net的特征提取网络替换成轻量级MobilenetV2网络,降低模型的参数和计算量;然后,为了提高U-Net的分割精度和鲁棒性,在网络结构中引入SE(squeeze and excitation)注意力模块;最后,使用最小外接矩阵得到零件的长宽基本参数,实现零件的识别和定位。试验表明,IU-Net相对于U-Net在平均交并比Miou(mean intersection over union)和像素准确率PA(pixel accuracy)分别提高4.39%和3.82%。在处理图像时,IU-Net相对于U-Net速度提升76.92%。与主流分割模型相比,IU-Net实现了更好的分割效果,有效地提高了小型机械零件的分割精度。在抓取试验中,IU-Net-MBR在识别率和抓取率上分别达到了100%和96.67%。
基金Supported by the National High Technology Research and Development Program of China(No.2013AA013501)the National Program on Key Basic Research Project(No.2012CB315801)+1 种基金the National Natural Science Foundation of China(No.61133015)the Science and Technology on Information Transmission and Dissemination in Communication Networks Laboratory,CETC54
文摘The scalability of routing architectures for large networks is one of the biggest challenges that the Internet faces today.Greedy routing,in which each node is assigned a locator used as a distance metric,recently received increased attention from researchers and is considered as a potential solution for scalable routing.In this paper,LMD—a local minimum driven method is proposed to compute the topology-based locator.To eliminate the negative effect of the " quasi" greedy property—transfer routes longer than the shortest routes,a two-stage routing strategy is introduced,which combines the greedy routing with source routing.The greedy routing path discovered and compressed in the first stage is then used by the following source-routing stage.Through extensive evaluations,based on synthetic topologies as well as on a snapshot of the real Internet AS(autonomous system)topology,it is shown that LMD guarantees 100%delivery rate on large networks with low stretch.
基金The National Natural Science Foundation of China under contract No.42001401the China Postdoctoral Science Foundation under contract No.2020M671431+1 种基金the Fundamental Research Funds for the Central Universities under contract No.0209-14380096the Guangxi Innovative Development Grand Grant under contract No.2018AA13005.
文摘The back propagation(BP)neural network method is widely used in bathymetry based on multispectral satellite imagery.However,the classical BP neural network method faces a potential problem because it easily falls into a local minimum,leading to model training failure.This study confirmed that the local minimum problem of the BP neural network method exists in the bathymetry field and cannot be ignored.Furthermore,to solve the local minimum problem of the BP neural network method,a bathymetry method based on a BP neural network and ensemble learning(BPEL)is proposed.First,the remote sensing imagery and training sample were used as input datasets,and the BP method was used as the base learner to produce multiple water depth inversion results.Then,a new ensemble strategy,namely the minimum outlying degree method,was proposed and used to integrate the water depth inversion results.Finally,an ensemble bathymetric map was acquired.Anda Reef,northeastern Jiuzhang Atoll,and Pingtan coastal zone were selected as test cases to validate the proposed method.Compared with the BP neural network method,the root-mean-square error and the average relative error of the BPEL method can reduce by 0.65–2.84 m and 16%–46%in the three test cases at most.The results showed that the proposed BPEL method could solve the local minimum problem of the BP neural network method and obtain highly robust and accurate bathymetric maps.
文摘Sichuan Province,East Western of China,within the area of east longitude 97°21′-108°31′,north latitude 26°03′-34°19′,which is on the Mediterranean seismic zone;with its complicated geological background,several strong shocks occurred in this district since ancient times.Earthquake catalogue of this area could date back to B.C.26,however,limited by the conditions—technology or funds,lots of minor earthquake have been lost,which could be