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Human Following for Outdoor Mobile Robots Based on Point-Cloud's Appearance Model

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Chinese Journal of Electronics 2021年第6期30卷 1087-1095页

作者： GONG Linxi CAI Yunfei school of computer science and engineering Nanjing University of Science and Technology

In this paper, we propose a point-cloudbased algorithm for human-following robots to detect and follow the target person in a complex outdoor environment. Specifically, we exploit Ada Boost to train a binary classifier in a designed feature space based on sparse point-cloud to distinguish the target person from other objects. Then a particle filter is applied to continuously track the target’s position. Motivated by the interference of obstacles in long-distance human-following scenarios, a motion plan algorithm based on vector field histogram is adopted. Experiments are carried out both on the dataset we collected and in real application scenarios. The results show that our algorithm has the ability of real-time target detection and tracking, and is robust to deal with complex situations in outdoor environments.

关键词： outdoor environments outdoor mobile robots particle filter target person point-cloud-based algorithm path planning collision avoidance designed feature space binary classifier mobile robots tracking real-time target detection particle filtering (numerical methods) sparse point-cloud learning (artificial intelligence) complex outdoor environment motion plan algorithm vector field histogram object detection

Semi-supervised local feature selection for data classification

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science China(Information sciences) 2021年第9期64卷 127-138页

作者： Zechao LI Jinhui TANG school of computer science and engineering Nanjing University of Science and Technology

Conventional feature selection methods select the same feature subset for all classes, which means that the selected features might work better for some classes than the others. Towards this end, this paper proposes a new semi-supervised local feature selection method(S2 LFS) allowing to select different feature subsets for different classes. According to this method, class-specific feature subsets are selected by learning the importance of features considering each class separately. In particular, the class labels of all available data are jointly learned under a consistent constraint over the labeled data, which enables the proposed method to select the most discriminative features. Experiments on six data sets demonstrate the effectiveness of the proposed method compared to some popular feature selection methods.

关键词： local feature selection label-specific feature semi-supervised learning data classification discriminative feature

LKLR: A Local Tangent Space-Alignment Kernel Least-Squares Regression Algorithm

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Tsinghua science and technology 2019年第4期24卷 389-399页

作者： Chao Tan Genlin Ji the school of computer science and engineering Southeast University the school of computer science and technology Nanjing Normal University the school of computer science and technology Nanjing Normal University

In the fields of machine learning and data mining, label learning is a nascent area of research, and within this paradigm, there is much room for improving multi-label manifold learning algorithms for high-dimensional data. Thus far, researchers have experimented with mapping relationships from the feature space to the traditional logical label space(using neighbors in the label space, for example, to predict logical label vectors from the feature space's manifold structure). Here we combine the feature manifold's and label space's local topological structures to reconstruct the label manifold. To achieve this, we use a nonlinear manifold learning algorithm to transform the local topological structure from the feature space to the label space. Our algorithm adopts a regularized leastsquares kernel method to realize the reconstruction process, employing an optimization function to find the best solution. Extensive experiments show that our algorithm significantly improves multi-label manifold learning in terms of learning accuracy and time complexity.

关键词： multi-label manifold learning local topological structure regularized least squares kernel method

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GridNet-3D: A Novel Real-Time 3D Object Detection Algorithm Based on Point Cloud

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Chinese Journal of Electronics 2021年第5期30卷 931-939页

作者： YUE Yuanchen CAI Yunfei WANG Dongsheng school of computer science and engineering Nanjing University of Science and Technology

3D object detection based on point cloud has an important application prospect in automatic driving technology. Aiming at the low precision of 3D object detection based on point cloud and the poor real-time performance caused by large numbers of 3D convolutions, a novel end-to-end real-time object detection algorithm named GridNet-3D is proposed. In the work, 2D gridmapping is used to preprocess the original point *** a novel structure grid encoding layer is adopted to encode point cloud features and is gotten grid feature maps in bird's eye view which is connected to region proposal network module to generate detections. Despite only using point clouds, the results on the KITTI 3D detection benchmark show that our algorithm has higher detection precision and better real-time performance on the detection of cars, pedestrians and cyclists, which has high practical value.

关键词： GridNet-3D point cloud features region proposal network module structure grid encoding layer grid feature maps 2D gridmapping intelligent transportation systems end-to-end real-time object detection algorithm KITTI 3D detection benchmark feature extraction automatic driving technology object detection 3D convolution

Sulfolane‑Based Flame‑Retardant Electrolyte for High‑Voltage Sodium‑Ion Batteries

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Nano-Micro Letters 2025年第2期17卷 498-516页

作者： Xuanlong He Jie Peng Qingyun Lin Meng Li Weibin Chen Pei Liu Tao Huang Zhencheng Huang Yuying Liu Jiaojiao Deng Shenghua Ye Xuming Yang Xiangzhong Ren Xiaoping Ouyang Jianhong Liu Biwei Xiao Jiangtao Hu Qianling Zhang Graphene Composite Research Center College of Chemistry and Environmental EngineeringShenzhen UniversityShenzhen 518060People’s Republic of China Center of Electron Microscopy State Key Laboratory of Silicon and Advanced Semiconductor MaterialsSchool of Materials Science and EngineeringZhejiang UniversityHangzhou 310027People’s Republic of China GRINM(Guangdong)Research Institute for Advanced Materials and technology FoshanGuangdong 528051People’s Republic of China College of Energy engineering Zhejiang UniversityHangzhouZhejiang 310027People’s Republic of China school of Materials science and engineering Xiangtan UniversityXiangtan 411105People’s Republic of China Shenzhen Eigen-Equation Graphene technology Co.Ltd Shenzhen 518000People’s Republic of China

Sodium-ion batteries hold great promise as next-generation energy storage ***,the high instability of the electrode/electrolyte interphase during cycling has seriously hindered the development of *** particular,an unstable cathode–electrolyte interphase(CEI)leads to successive electrolyte side reactions,transition metal leaching and rapid capacity decay,which tends to be exacerbated under high-voltage ***,constructing dense and stable CEIs are crucial for high-performance *** work reports localized high-concentration electrolyte by incorporating a highly oxidation-resistant sulfolane solvent with non-solvent diluent 1H,1H,5H-octafluoropentyl-1,1,2,2-tetrafluoroethyl ether,which exhibited excellent oxidative stability and was able to form thin,dense and homogeneous *** excellent CEI enabled the O3-type layered oxide cathode NaNi_(1/3)Mn_(1/3)Fe_(1/3)O_(2)(NaNMF)to achieve stable cycling,with a capacity retention of 79.48%after 300 cycles at 1 C and 81.15%after 400 cycles at 2 C with a high charging voltage of 4.2 *** addition,its nonflammable nature enhances the safety of *** work provides a viable pathway for the application of sulfolane-based electrolytes on SIBs and the design of next-generation high-voltage electrolytes.

关键词： Sodium-ion batteries Sulfolane-based electrolyte High voltage Layered oxide cathode Flame retardant

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An Intelligent Scheduling Approach for Electric Power Generation

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Chinese Journal of Electronics 2018年第6期27卷 1170-1175页

作者： YU Li JIN Xin LI Zeng XIONG Yan HUANG Wenchao College of computer science and engineering Anhui University of Science and Technology school of computer science and technology University of Science and Technology of China

Although China is vigorously developing clean energy and nuclear power, the thermal power generation(mainly coal power) is still the most important power generation method at present. Economic load dispatch(ELD) is a typical optimization problem in power systems which lots of researchers are trying to *** purpose of ELD is to increase the efficiency of thermal power generation under the conditions of load and operational constraints. When it comes to power generation scheduling, manual operation is still the main form,which is inefficient. In order to use a large amount of historical power generation data to improve the efficiency of power generation scheduling and achieve the effect of energy conservation, we propose an intelligent power generation scheduling system based on Deep neural networks(DNN) and Ant colony optimization(ACO). Experiments show that our DNN algorithm can predict the unit coal consumption precisely. Compared with the dynamic programming algorithm and equal differential increment rate algorithm, ACO can complete power generation scheduling tasks more quickly and efficiently.

关键词： Deep learning Ant colony optimization(ACO) Smart grid

A Novel Tree-Based Genetic Algorithm for the Multicast Protocol in Two-Tiered WSNs

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Chinese Journal of Electronics 2020年第5期29卷 852-858页

作者： ZHANG Qiongbing XIE Chengwang JIANG Lei school of computer science and engineering Hunan University of Science and Technology school of computer and Information engineering Nanning Normal University

Genetic algorithms(GAs) serve as a class of powerful tools to search for an effective multicast routing scheme among multiple cluster header nodes,which strongly affects the lifetime of two-tiered Wireless sensor networks(WSNs). This paper proposes a novel Genetic algorithm(GA) with a new crossover mechanism called Leaf crossover for the multicast routing among upper tier nodes in two-tiered WSNs, which outperforms the existing popular tree-based GAs by not requiring the global network link information, encoding/decoding or repair operations. Our simulation study indicates that the proposed algorithm could prolong the lifetime of multicast service, increase the packet delivery ratio as well as converge fast by comparison with existing GAs.

关键词： Wireless sensor networks (WSNs) Multicast Genetic algorithm (GA) Leaf crossover

Personalized Privacy-Preserving Trajectory Data Publishing

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Chinese Journal of Electronics 2017年第2期26卷 285-291页

作者： LU Qiwei WANG Caimei XIONG Yan XIA Huihua HUANG Wenchao GONG Xudong school of computer science and technology University of Science and Technology of China Department of computer science and engineering Hefei University

Due to the popularity of mobile internet and location-aware devices,there is an explosion of location and tra jectory data of moving objects.A few proposals have been proposed for privacy preserving tra jectory data publishing,and most of them assume the attacks with the same adversarial background *** practice,different users have different privacy *** non-personalized privacy assumption does not meet the personalized privacy requirements,meanwhile,it looses the chance to achieve better utility by taking advantage of differences of users’ privacy *** study the personalized tra jectory k-anonymity criterion for trajectory data ***,we explore and propose an overall framework which provides privacy preserving services based on users’ personal privacy requests,including tra jectory clustering,editing and *** demonstrate the efficiency and effectiveness of our scheme through experiments on real world dataset.

关键词： Personalization Tra jectory data Privacy-preserving data publishing

Construction of Ni single-atom coordinated with doped N and S elements for mild hydrogenation of methyl acrylate to methyl propionate

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Nano Research 2025年第1期18卷 217-224页

作者： Taolue Sun Chen Jian Gang Wang Hui Zhao Guoliang Zhang Zengxi Li Chunshan Li State Key Laboratory of Mesoscience and engineering CAS Key Laboratory of Green Process and EngineeringBeijing Key Laboratory of Ionic Liquids Clean ProcessInstitute of Process EngineeringChinese Academy of SciencesBeijing 100190China school of Chemical engineering University of Chinese Academy of SciencesBeijing 100049China Huizhou Institute of Green Energy and Advanced Materials Huizhou 516081China Advanced Energy science and technology Guangdong Laboratory Huizhou 516081China

Although the nickel-based catalyst is able toexhibit comparative catalytic activity to noble metal formethyl acrylate hydrogenation,it requires strict reactioncondition,which can be improved by regulation ofcoordination *** this study,we constructed akind of Ni single-atom coordinated with N and S(Ni-NSC)through the pyrolysis of organic Ni-based precursors at600℃.The existence and fine structure of Ni single-atom were confirmed by the spherical electron microscopicobservation in combination with the X-ray absorption spectroscopy(XAS)*** addition,the catalytichydrogenation assessment suggested that the as-prepared Ni-NSC catalyst exhibited higher activity and stability than theNi/NSC supported catalyst prepared by incipient wetness impregnation *** remarkable catalytic activity was dueto the high dispersion and density of Ni single-atom and weak adsorption energy of intermediates on these Ni sites.

关键词： methyl acrylate mild hydrogenation Ni single-atom coordination environment adsorption energy