检索结果-内蒙古大学图书馆

IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Jiwei Shan Yirui Li Qiyu Feng Ditao Li Lijun Han Hesheng Wang Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China School of Mechanical Engineering Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Building a self-model for robots, enabling them to simulate their physical selves and predict future states without direct interaction with the physical world, is crucial for robot motion planning and control. Existing self-modeling methods primarily focus on rigid robots and typically require significant time, effort, and resources to gather training data. In this study, we introduce SoftNeRF, a self-supervised visual self-model designed for soft robots. We use a hybrid neural shape representation based on the Signed Distance Function (SDF) to capture both the geometry and complex nonlinear motion of soft robots. By leveraging differentiable rendering, our method learns a self-model from readily available RGB images, similar to how humans understand their physical state through reflection. To improve training efficiency and model accuracy, we propose an error-guided adaptive sampling strategy. SoftNeRF can serve as a plug-in for various downstream tasks, even when trained with data unrelated to those tasks. We demonstrate SoftNeRF’s ability to support shape prediction and motion planning for robots in both simulated and real-world environments. Furthermore, SoftNeRF excels in detecting and recovering from damage, thereby enhancing machine resilience. Code is available at: https://***/irmvlab/soft-nerf.

关键词： Training Visualization Adaptation models Accuracy Shape Training data Soft robotics Rendering (computer graphics) Sampling methods Planning

来源：评论

学校读者我要写书评

暂无评论

Short-term load forecasting for buildings based on dynamic weighted edRVFL model

Short-term load forecasting for buildings based on dynamic w...

引用

2024 China Automation Congress, CAC 2024

作者： Xie, Junwei Yuan, Meng Xu, Zhezhuang Liu, Chi Xia, Yuxiong College of Electrical Engineering and Automation Fuzhou University Key Laboratory of Industrial Automation Control Technology and Information Processing Education Department of Fujian Province Fuzhou350000 China Fujian Huading Intelligent Manufacturing Technology Co. Ltd. Fuzhou350000 China

ISBN: (纸本)9798350368604

Short-term load forecasting of buildings plays a key role in demand management, however, when dealing with massive data, the prevalent practice of training and testing the system as a whole overlooks pattern variations inside data and potentially limits predictive performance. To address this issue, this paper proposes an ensemble deep random vector functional link (edRVFL) model that combines adaptive ensemble clustering and dynamic weighting strategy for load forecasting of an industrial building. Firstly, the adaptive ensemble clustering that combines ordering points to identify the clustering structure and K nearest neighbor is employed to determine the electricity load usage patterns. Subsequently, the improved particle swarm optimization algorithm is applied to adjust the weights of load curves in different typical day scenarios. Finally, a dynamic weighting strategy is designed to dynamically assign model weights to two clusters, where one matches the type of predicted load pattern for the day being forecasted and another for the cluster of the previous day. The experiment in a real building verifies the effectiveness of the proposed algorithm, which has higher prediction accuracy than other comparison algorithms including one-week interval and different ensemble clustering. © 2024 IEEE.

关键词： Particle swarm optimization (PSO)

来源：评论

学校读者我要写书评

暂无评论

A Multi-Stage Goal-Driven Network for Pedestrian Trajectory Prediction 5

A Multi-Stage Goal-Driven Network for Pedestrian Trajectory ...

引用

5th International Conference on Computer Vision, Image and Deep Learning, CVIDL 2024

作者： Wu, Xiuen Wang, Tao Cai, Yuanzheng Liang, Lingyu Papageorgiou, George Minjiang University Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Fuzhou China Fuzhou University College of Computer and Data Science Fuzhou China South China University of Technology School of Electronic and Information Engineering Guangzhou China European University Cyprus Department of Computer Science and Engineering Nicosia Cyprus

ISBN: (纸本)9798350373820

Pedestrian trajectory prediction plays a pivotal role in ensuring the safety and efficiency of various applications, including autonomous vehicles and traffic management systems. This paper proposes a novel method for pedestrian trajectory prediction, called multi-stage goal-driven network (MGNet). Diverging from prior approaches relying on stepwise recursive prediction and the singular forecasting of a long-term goal, MGNet directs trajectory generation by forecasting intermediate stage goals, thereby reducing prediction errors. The network comprises three main components: a conditional variational autoencoder (CVAE), an attention module, and a multi-stage goal evaluator. Trajectories are encoded using conditional variational autoencoders to acquire knowledge about the approximate distribution of pedestrians' future trajectories, and combined with an attention mechanism to capture the temporal dependency between trajectory sequences. The pivotal module is the multi-stage goal evaluator, which utilizes the encoded feature vectors to predict intermediate goals, effectively minimizing cumulative errors in the recursive inference process. The effectiveness of MGNet is demonstrated through comprehensive experiments on the JAAD and PIE datasets. Comparative evaluations against state-of-the-art algorithms reveal significant performance improvements achieved by our proposed method. © 2024 IEEE.

关键词： Trajectories

来源：评论

学校读者我要写书评

暂无评论

Solving Constrained Multi-objective Optimization Problems with Passive Archiving Mechanism 1

引用

17th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2022

作者： Jia, Huijuan Zhang, Kai Shen, Chaonan School of Computer Science and Technology Wuhan University of Science and Technology Wuhan430065 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System Wuhan University of Science and Technology Wuhan430065 China

ISBN: (数字)9789819915491

ISBN: (纸本)9789819915484

During these years, many advanced constrained multi-objective evolutionary algorithms (CMOEAs) have been developed to solve constrained multi-objective optimization problems (CMOPs). However, some existing constrained multi-objective algorithms do not use an archiving mechanism, which leads to easy loss of the searched feasible solutions during the search process. In addition, even if some algorithms use an archiving mechanism, an unsuitable archiving update strategy can cause difficulty in balancing the diversity and convergence of the archive set. To address these challenges, a two-stage constrained multi-objective evolutionary algorithm based on a passive archiving mechanism (PA-CMOEA) is proposed in this paper. In the first stage, the constrained multi-objective problem is modeled as an unconstrained multi-objective problem, which allows the population to fully explore the decision space. The archive set is passively updated in a constraint-domination principle (CDP) criterion using population information. The goal of this stage is for the archive set to converge to the constrained Pareto front region of the problem with the help of population information. In the second stage, a local search is performed on the archive set. Specifically, the convergence and diversity of the archived solution set is improved while ensuring that the feasibility of the archived set is not worse. Finally, the algorithm outputs the archive set. To estimate the performance of the proposed algorithm, experiments are conducted on the LIRCMOP and CF benchmarks in comparison with some of the most popular algorithms. The experimental results demonstrate that the proposed algorithm has a competitive advantage compared with the comparative algorithms. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Benchmarking

来源：评论

学校读者我要写书评

暂无评论

Enhanced fireworks algorithm based on particle swarm optimization and reverse learning of small-hole imaging experiment

Enhanced fireworks algorithm based on particle swarm optimiz...

引用

2022 IEEE International Conference on systems, Man, and Cybernetics, SMC 2022

作者： Jiao, Jiao Li, Jun Wuhan University of Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System College of Computer Science and Technology Wuhan China

ISBN: (数字)9781665452588

ISBN: (纸本)9781665452588

Since the traditional fireworks algorithm (FWA) is easy to fall into local optimization and has insufficient global optimization capability and low optimization accuracy, this paper proposes the enhanced fireworks algorithm (EFWA-SI) based on particle swarm optimization and small-hole imaging reverse learning. First, a dynamic explosion amplitude mechanism based on the evolution speed of the population is designed. The evolution speed of the population is dynamically adjusted by evaluating the evolution speed of the fitness in each iteration process, and the global and local search information is controlled. Secondly, the small-hole imaging reverse learning strategy combined with the idea of optimal-worst reverse learning is proposed. This strategy increases the diversity of the optimal-seeking positions and improves the ability of the algorithm to jump out of the local optimum;Finally, the current position is updated according to the position and speed of each firework, and the globally optimal fireworks and personally optimal fireworks are updated simultaneously to improve the individual heuristic learning ability. Through the simulation experiments on the CEC2015 test function and comparison with related algorithms, the results show that the algorithm performs better in convergence speed, computational accuracy, and stability. © 2022 IEEE.

关键词： Global optimization

来源：评论

学校读者我要写书评

暂无评论

Robust optimization-based fusion of GNSS and Visual-Inertial-Wheel Odometry

Robust optimization-based fusion of GNSS and Visual-Inertial...

引用

2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022

作者： Hou, Jake Jie Wu, Xinrui Shan, Jiwei Li, Dun Wang, Hesheng Shanghai Jiao Tong University Department of Automation China Shanghai Karlang Industrial Nantong Intelligent Technology Co. Ltd China Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Department of Automation Shanghai200240 China

ISBN: (纸本)9781665481090

SLAM is significant to autonomous mobile robots. In order to realize drift-free state estimation and provide accurate localization results for the subsequent navigation, we develop an optimization-based framework consisting of a high-frequency Inertial-Wheel Odometry(IWO), Visual-Inertial-Wheel Odometry(VIWO) and a global fusion module. To fuse the local state with the position provided by GNSS, we perform ternary edge in factor graph optimization to estimate the transformation between the local frame and ENU coordinate. Thanks to the tightly-coupled VIWO, the localization property of the odometry presents more robustness, and improve the accuracy of global fusion. A noise repropagation strategy is introduced to ensure the consistency of the IMU and wheel odometer. We evaluate the proposed system on public datasets and test it in real-world scenario. The experimental results show that our system achieves accurate pose estimation in outdoor environments. © 2022 IEEE.

关键词： Frequency estimation

来源：评论

学校读者我要写书评

暂无评论

Communication and Computation Resource Allocation for Digital Twin in IIoT systems

Communication and Computation Resource Allocation for Digita...

引用

2021 China Automation Congress, CAC 2021

作者： Ren, Cheng Chen, Cailian Li, Peizhe Guan, Xinping Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China

ISBN: (纸本)9781665426473

In order to construct the digital twin (DT) of the manufacturing process in industrial IoT (IIoT) systems, multiple sensors and IIoT equipments (IIEs) are deployed for process monitoring (PM) and other tasks. Heterogeneous data generated from different tasks are transmitted through the shared wireless network to edge computing devices (ECDs) for further decisions. However, either communication or computation resources are limited in industrial environment, which should be allocated efficiently. In this paper, in order to improve the overall efficiency for DT construction, we adjust transmission power, allocate bandwidth and determine computing resource allocation for various tasks, which are jointly optimized by formulating a mixed integer nonlinear programming (MINLP) problem. We decompose the original problem into two subproblems and propose a value-of-information (Vol) based algorithm for PM tasks. Then, we characterize the relationship between state estimation convergence for PM and the maximum allowed offloading aomunt for other computation tasks at each time slot. Based on that relationship, we determine the transmission power and the computing resource allocation policy for IIEs. Finally, simulation results prove that our method can improve the overall efficiency while guaranteeing state estimation convergence requirements for PM systems and stability of computation task queues for other tasks. © 2021 IEEE

关键词： Resource allocation

来源：评论

学校读者我要写书评

暂无评论

DDS-SLAM: Dense Semantic Neural SLAM for Deformable Endoscopic Scenes

DDS-SLAM: Dense Semantic Neural SLAM for Deformable Endoscop...

引用

IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Jiwei Shan Yirui Li Lujia Yang Qiyu Feng Lijun Han Hesheng Wang Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China School of Mechanical Engineering Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Estimating camera motion and continuously reconstructing dense scenes in deformable environments presents a complex and open challenge. Many existing approaches tend to rely on assumptions about the scene’s topology or the nature of deformable motion. However, these assumptions do not hold true in medical endoscopy applications. To address these challenges, we introduce DDS-SLAM, a novel dense deformable semantic neural SLAM that achieves accurate camera tracking, continuous dense scene reconstruction, and high-quality image rendering in deformable scenes. First, we propose a novel hybrid neural scene representation method capable of capturing both natural and artificial deformations. Additionally, by leveraging the 2D semantic information of the scene, we introduce a semantic loss function based on semantic distance fields. This approach guides network optimization at a higher level, thereby enhancing system performance. Furthermore, we validate our method through a series of experiments conducted on several representative medical datasets, demonstrating its superiority over other state-of-the-art approaches. The code is available at: https://***/IRMVLab/DDS-SLAM.

关键词： Simultaneous localization and mapping Tracking system performance Semantics Cameras Rendering (computer graphics) Topology Image reconstruction Optimization Biomedical imaging

来源：评论

学校读者我要写书评

暂无评论

Research on low energy task allocation and scheduling algorithm based on imprecise heterogeneous multi-core technology

Research on low energy task allocation and scheduling algori...

引用

2022 IEEE International Conference on systems, Man, and Cybernetics, SMC 2022

作者： Gu, Haonan Wu, Jing Hu, Wei Ma, Tianao Wuhan University of Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System College of Computer Science and Technology Wuhan China

ISBN: (数字)9781665452588

ISBN: (纸本)9781665452588

In heterogeneous embedded systems, we try to find a new non real-time scheduling algorithm, which can not only meet the reliability requirements, but also achieve low energy consumption. 'Resource reservation time deterministic cyclic scheduling (RRTDCS)' algorithm is a kind of scheduling for offline cache pre-allocation. This scheduling algorithm combines time reservation and priority strategy. The algorithm can dynamically adjust according to different task sets. It can also adjust its own scheduling process to adapt to different scheduling environments. The periodic cyclic strategy enables low power consumption in task allocation. In the experimental part, we compared the algorithm proposed in this paper with the current mainstream real-time scheduling scheme. Experimental results show that RRTDCS algorithm has better performance. © 2022 IEEE.

关键词： Scheduling

来源：评论

学校读者我要写书评

暂无评论

Self-powered temperature-changing system driven by wind energy

引用

Microsystems & Nanoengineering 2024年第5期10卷 171-180页

作者： Jiayu Li Boxun Liu Mingyang Li Yahui Li Wangyang Ding Guanlin Liu Jun Luo Nan Chen Lingyu Wan Wenjuan Wei Center on Nanoenergy Research Institute of Science and Technology for Carbon Peak&NeutralityGuangxi UniversityNanning 530004China State Key Laboratory of Featured Metal Materials and Life-cycle Safety for Composite Structures School of Physical Science&TechnologyGuangxi UniversityNanning 530004China Department of Chemistry and the Tsinghua Center for Frontier Polymer Research Tsinghua UniversityBeijing 100084PR China State Key Laboratory of Pollution Control and Resource Reuse School of the EnvironmentNanjing UniversityNanjing 210023China Department of Micro/Nano Electronics School of Electronic Information and Electrical EngineeringShanghai Jjao Tong UniversityShanghai 200240PR China State Key Laboratory of Featured Metal Materials and Life-cycle Safety for Composite Structures MOE Key Laboratory of New Processing Technology for Nonferrous Metals and Materialsand School of ResourcesEnvironment and MaterialsGuangxi UniversityNanning 530004China

Research on outdoor,mobile,and self-powered temperature-control devices has always been highly *** devices can reduce energy consumption for cooling and heating,and they have broad market *** this basis,a rotary disc-shaped triboelectric nanogenerator(TENG)with a maximum open-circuit voltage of 6913 V,a maximum short-circuit current of 85μA,and a maximum transferred charge of 1.3μC was *** synthesized a ferroelectric ceramic composed of 0.15PbTiO_(3)-0.85PbSc_(o.5)Ta_(o.5)O_(3)(0.15PT-0.85PST),which exhibited excellent electrothermal effects at room *** quenching,the electrothermal effect(A Tmax)and energy harvesting properties of the device were 1.574 K and 0.542 J/cm3,***,for the frst time,we proposed a self-powered temperature quantification control system with a rotary disc-shaped *** device effectively harnessed wind and water energy,in addition to other types of *** system consisted of energy collecting cups,a rotating disc-shaped FEP-rabbit fur TENG,a circuit management module,and a ferroelectric ceramic chip *** the circuit management module,the system converted external wind energy into a high-voltage electric field at the two ends of the 0.15PT-0.85PST ceramic chip to fully stimulate the electrothermal *** a speed of 200 rpm,the temperature change in the insulated cup within 276 s was 0.49 K,and the volume of the insulated cup was 300 times greater than that of the 0.15PT-0.85PST ceramic *** with the results reported in previous work,the cooling and heating times were both reduced by 31%,and the temperature changes for both cooling and heating increased by 81%.Moreover,the heating and cooling temperatures of the device optimized on this basis were increased to 1.19K and 0.93 K,*** great improvement in the temperature variation performance confrmed the great potential of the device for *** research could serve as a reference for reduci

关键词： ceramic shaped ferroelectric

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：