检索结果-内蒙古大学图书馆

IEEE/ASME (AIM) International Conference on Advanced Intelligent Mechatronics

作者： Enhao Zheng Jinchen Zeng Dongfang Xu Qining Wang Hong Qiao State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences No. 95 of Zhongguancun East Road Beijing China School of Automation and Electrical Engineering University of Science and Technology Beijing 30 Xueyuan Road Beijing Robotics Research Group College of Engineering Peking University Beijing China

ISBN: (数字)9781728167947

ISBN: (纸本)9781728167954

Noncontact captive sensing is a new sensing strategy that we proposed previously to compensate for the limitations of existing surface electromyography studies for exoskeleton control. It has been validated on locomotion mode recognition and gait phase estimation. However, our previous studies addressed the tasks of periodic ambulation based on machine learning algorithms. The performances of the capacitive sensing on non-periodical lower-limb motion recognition have never been evaluated. In this preliminary study, we designed a motion recognition method by fusing the capacitive sensing and the inertial sensors. The recognition algorithm was designed based on the combined logics, which freed the system from burdensome training procedures in the recognition tasks. The method was validated on three healthy subjects in performing 6 lower-limb motions and the transitions between them (10 in total). The capacitance-inertial fusion method produced an average precision/recall of >0.92 in static motions and >0.86 with transitions. The most prominent improvement of using the capacitance signals is that it increases the time-response ability during the motion transitions. Compared with purely using inertial sensors, the sensor fusion method reduced more than 100-ms latency on average. The pilot study extends the scope of the new sensing method in human motion recognition. Future efforts will be paid in this direction to get more promising results.

关键词： Robot sensing systems Capacitance Electrodes Task analysis Legged locomotion Exoskeletons

来源：评论

学校读者我要写书评

暂无评论

Real-time Whole-body Motion Planning for Mobile Manipulators Using Environment-adaptive Search and Spatial-temporal Optimization

Real-time Whole-body Motion Planning for Mobile Manipulators...

引用

IEEE International Conference on robotics and Automation (ICRA)

作者： Chengkai Wu Ruilin Wang Mianzhi Song Fei Gao Jie Mei Boyu Zhou School of Artificial Intelligence Sun Yat-Sen University Zhuhai China School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen Shenzhen China State Key Laboratory of Industrail Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Mobile manipulators have recently gained significant attention in the robotics community due to their superior potential in industrial and service applications. However, the high degree of freedom associated with mobile manipulators poses challenges in achieving real-time whole-body motion planning. To bridge the gap, this paper presents a motion planning method capable of generating high-quality, safe, agile and feasible trajectories for mobile manipulators in real time. First, we present a novel environment-adaptive path searching method, which can generate paths in real-time in various environments by adaptively adjusting searching dimension based on environment complexity. Additionally, we propose a real-time spatial-temporal trajectory optimization method that takes into account the whole-body safety, agility and dynamic feasibility of mobile manipulators. Moreover, task constraints are applied to ensure that the trajectory can fulfill specific task requirements. Simulation and real-world experiments demonstrate that our method is capable of generating whole-body trajectories in real-time in challenging environments. We will release our code to benefit the community.

关键词： Service robots Dynamics Transportation Real-time systems Planning Safety Complexity theory

来源：评论

学校读者我要写书评

暂无评论

NF-Atlas: Multi-Volume Neural Feature Fields for Large Scale LiDAR Mapping

arXiv

引用

arXiv 2023年

作者： Yu, Xuan Liu, Yili Mao, Sitong Zhou, Shunbo Xiong, Rong Liao, Yiyi Wang, Yue The State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China College of Information Science and Electronic Engineering Zhejiang University Hangzhou China Huawei Cloud Computing Technologies Co. Ltd. Shenzhen China

LiDAR Mapping has been a long-standing problem in robotics. Recent progress in neural implicit representation has brought new opportunities to robotic mapping. In this paper, we propose the multi-volume neural feature fields, called NF-Atlas, which bridge the neural feature volumes with pose graph optimization. By regarding the neural feature volume as pose graph nodes and the relative pose between volumes as pose graph edges, the entire neural feature field becomes both locally rigid and globally elastic. Locally, the neural feature volume employs a sparse feature Octree and a small MLP to encode the signed distance function (SDF) of the submap with an option of semantics. Learning the map using this structure allows for end-to-end solving of maximum a posteriori (MAP) based probabilistic mapping. Globally, the map is built volume by volume independently, avoiding catastrophic forgetting when mapping incrementally. Furthermore, when a loop closure occurs, with the elastic pose graph based representation, only updating the origin of neural volumes is required without remapping. Finally, these functionalities of NF-Atlas are validated. Thanks to the sparsity and the optimization based formulation, NF-Atlas shows competitive performance in terms of accuracy, efficiency and memory usage on both simulation and real-world datasets. The project page is: https://***/NFAtlas/ Copyright © 2023, The Authors. All rights reserved.

关键词： Mapping

来源：评论

学校读者我要写书评

暂无评论

Online, Target-Free LiDAR-Camera Extrinsic Calibration via Cross-Modal Mask Matching

arXiv

引用

arXiv 2024年

作者： Huang, Zhiwei Zhang, Yikang Chen, Qijun Fan, Rui The Department of Control Science & Engineering The College of Electronics & Information Engineering Shanghai Institute of Intelligent Science and Technology Shanghai Research Institute for Intelligent Autonomous Systems The State Key Laboratory of Intelligent Autonomous Systems Frontiers Science Center for Intelligent Autonomous Systems Tongji University Shanghai201804 China

LiDAR-camera extrinsic calibration (LCEC) is crucial for data fusion in intelligent vehicles. Offline, target-based approaches have long been the preferred choice in this field. However, they often demonstrate poor adaptability to real-world environments. This is largely because extrinsic parameters may change significantly due to moderate shocks or during extended operations in environments with vibrations. In contrast, online, target-free approaches provide greater adaptability yet typically lack robustness, primarily due to the challenges in cross-modal feature matching. Therefore, in this article, we unleash the full potential of large vision models (LVMs), which are emerging as a significant trend in the fields of computer vision and robotics, especially for embodied artificial intelligence, to achieve robust and accurate online, target-free LCEC across a variety of challenging scenarios. Our main contributions are threefold: we introduce a novel framework known as MIAS-LCEC, provide an open-source versatile calibration toolbox with an interactive visualization interface, and publish three real-world datasets captured from various indoor and outdoor environments. The cornerstone of our framework and toolbox is the cross-modal mask matching (C3M) algorithm, developed based on a state-of-the-art (SoTA) LVM and capable of generating sufficient and reliable matches. Extensive experiments conducted on these real-world datasets demonstrate the robustness of our approach and its superior performance compared to SoTA methods, particularly for the solid-state LiDARs with super-wide fields of view. Our toolbox and datasets are publicly available at ***/MIAS-LCEC. Copyright © 2024, The Authors. All rights reserved.

关键词： Cameras

来源：评论

学校读者我要写书评

暂无评论

Position Sensorless control of Permanent Magnet Synchronous Motor Based on Adaptive Sliding Mode Observer

Position Sensorless Control of Permanent Magnet Synchronous ...

引用

Chinese Automation Congress (CAC)

作者： Tao Zhang Yingjie Xiong Bolun Wang Hongyu Yan Xiyou Chen School of Electrical Engineering Dalian University of Technology Dalian China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China College Of Information Science and Engineering Northeastern University Shenyang China School of Artificial Intelligence Shenyang University of Technology Shenyang China

ISBN: (纸本)9781665426480

Permanent magnet synchronous motors(PMSM) are popular in AC motor applications due to their small size, high efficiency. They have appeared widely in various areas of life. Due to the high-frequency chattering problem caused by sliding mode observer sensorless control of PMSM, an SMO with piecewise control function is designed in this paper. At the same time, based on the back EMF output of the SMO, the gain of the SMO is adapted to reduce the system bucket vibration problem caused by the conventional SMO. Finally, a simulation experiment was carried out in MATLAB/SIMULINK and compared with the conventional SMO. The results show that the improved SMO has achieved a better control effect.

关键词： Vibrations Adaptation models AC motors Force Sensorless control Observers Permanent magnet motors

来源：评论

学校读者我要写书评

暂无评论

Real-Time Energy Management of Microgrid System Based on Policy-Based Reinforcement Learning

SSRN

引用

SSRN 2022年

作者： Liu, Ding Zang, Chuanzhi Zeng, Peng Li, Wanting Wang, Xin Liu, Yuqi Xu, Shuqing Key Laboratory of Networked Control System Chinese Academy of Sciences Shenyang110016 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institute of Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China Shenyang University of Technology Shenyang110870 China

Electric power grids are changing from traditional power systems to modern smart integrated power systems. The microgrid (MG) plays a vital role in this process through the integration of distributed renewable energy resources (RESs) and energy storage systems (ESSs). However, wind and solar radiation are characterized by intermittence, randomness and fluctuation. These uncertainties cannot be ignored in microgrids with high penetration of RES and random load demand, which challenges the effective and economic management of MGs. To achieve real-time economically optimal scheduling of microgrids, we proposed a real-time energy management strategy. Unlike traditional model-based approaches, this strategy is learning-based and does not need the knowledge of system uncertainties. The energy management problem of a microgrid is formulated as a Markov decision process (MDP) solved using policybased deep reinforcement learning (DRL). In the proposed RL-based approach, two different neural networks are used. One takes the real-time system state of the microgrid as inputs and makes the decision to obtain the optimal control policy © 2022, The Authors. All rights reserved.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

key Parameters Prediction for Intelligent control and Energy Optimization Based on MIC-BWO-XGBoost

Key Parameters Prediction for Intelligent Control and Energy...

引用

Cyber-Energy systems and Intelligent Energy (ICCSIE), International Conference on

作者： Changyao Lv Yaqi Wang Yudong Chen Zhuo Yu Guoliang Hu Hongliang Wu Shuai Li Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China Shanghai Aircraft Manufacturing Co. Ltd. Shanghai China College of Information Engineering Shenyang University of Chemical Technology Shenyang China

ISBN: (数字)9798350373318

ISBN: (纸本)9798350373325

In the aviation industry, anodic oxidation serves as a core process for surface modification of aluminum alloy components, albeit accompanied by high energy consumption. Accurate prediction of key parameters can offer decision support for the intelligent control and energy optimization of anodic oxidation. However, the limited sample size resulting from the high cost of data collection and the complex nonlinear patterns caused by the synergy of multiple factors pose a challenge in accurately predicting key parameters. Therefore, we propose a key parameters prediction method based on the Maximum Information Coefficient (MIC), Beluga Whale Optimization algorithm (BWO), and XGBoost algorithm. Considering the adverse impact of low correlation parameters on prediction accuracy, we first use MIC to extract features from the original data. Then, XGBoost is used to integrate multiple decision trees to ensure the strong fitting ability for nonlinear relationships. Compared to deep learning models, XGBoost performs well even in a limited sample size. In addition, considering XGBoost is prone to overfitting training data as an ensemble learning algorithm, we employ the BWO to optimize four key parameters of the model that are difficult to choose, thereby enhancing model's generalization. The model's performance is evaluated using Mean Squared Error (MSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE), with values of 0.04388, 0.09410, and 0.20730%, respectively. The experimental results demonstrate that the proposed method outperforms traditional approaches, enabling precise prediction of key parameters and holding significant value for the intelligent control and energy optimization of anode oxidation processes.

关键词： Microwave integrated circuits Accuracy Process control Prediction algorithms Feature extraction Data models Whale optimization algorithms Oxidation Optimization Intelligent control

来源：评论

学校读者我要写书评

暂无评论

PanoVpr: Towards Unified Perspective-to-Equirectangular Visual Place Recognition via Sliding Windows Across the Panoramic View

PanoVpr: Towards Unified Perspective-to-Equirectangular Visu...

引用

International Conference on Intelligent Transportation

作者： Ze Shi Hao Shi Kailun Yang Zhe Yin Yining Lin Kaiwei Wang State Key Laboratory of Modern Optical Instrumentation Zhejiang University Hangzhou China Shanghai SUPREMIND Technology Co. Ltd Shanghai China National Engineering Research Center of Robot Visual Perception and Control Technology School of Robotics Hunan University Changsha China

Visual place recognition has gained significant attention in recent years as a crucial technology in autonomous driving and robotics. Currently, the two main approaches are the perspective view retrieval (P2P) paradigm and the equirectangular image retrieval (E2E) paradigm. However, it is practical and natural to assume that users only have consumer-grade pinhole cameras to obtain query perspective images and retrieve them in panoramic database images from map providers. To address this, we propose PanoVPR, a perspective-to-equirectangular (P2E) visual place recognition framework that employs sliding windows to eliminate feature truncation caused by hard cropping. Specifically, PanoVPR slides windows over the entire equirectangular image and computes feature descriptors for each window, which are then compared to determine place similarity. Notably, our unified framework enables direct transfer of the backbone from P2P methods without any modification, supporting not only CNNs but also Transformers. To facilitate training and evaluation, we derive the Pitts250k-P2E dataset from the Pitts250k and establish YQ360, latter is the first P2E visual place recognition dataset collected by a mobile robot platform aiming to simulate real-world task scenarios better. Extensive experiments demonstrate that PanoVPR achieves state-of-the-art performance and obtains 3.8% and 8.0% performance gain on Pitts250k-P2E and YQ360 compared to the previous best method, respectively. Code and datasets will be publicly available at PanoVPR.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Minimalist and High-Quality Panoramic Imaging with PSF-aware Transformers

arXiv

引用

arXiv 2023年

作者： Jiang, Qi Gao, Shaohua Gao, Yao Yang, Kailun Yi, Zhonghua Shi, Hao Sun, Lei Wang, Kaiwei The State Key Laboratory of Modern Optical Instrumentation The National Engineering Research Center of Optical Instrumentation Zhejiang University Hangzhou310027 China The School of Robotics The National Engineering Research Center of Robot Visual Perception and Control Technology Hunan University Changsha410082 China

High-quality panoramic images with a Field of View (FoV) of 360° are essential for contemporary panoramic computer vision tasks. However, conventional imaging systems come with sophisticated lens designs and heavy optical components. This disqualifies their usage in many mobile and wearable applications where thin and portable, minimalist imaging systems are desired. In this paper, we propose a Panoramic Computational Imaging Engine (PCIE) to achieve minimalist and high-quality panoramic imaging. With less than three spherical lenses, a Minimalist Panoramic Imaging Prototype (MPIP) is constructed based on the design of the Panoramic Annular Lens (PAL), but with low-quality imaging results due to aberrations and small image plane size. We propose two pipelines, i.e. Aberration Correction (AC) and Super-Resolution and Aberration Correction (SR&AC), to solve the image quality problems of MPIP, with imaging sensors of small and large pixel size, respectively. To leverage the prior information of the optical system, we propose a Point Spread Function (PSF) representation method to produce a PSF map as an additional modality. A PSF-aware Aberration-image Recovery Transformer (PART) is designed as a universal network for the two pipelines, in which the self-attention calculation and feature extraction are guided by the PSF map. We train PART on synthetic image pairs from simulation and put forward the PALHQ dataset to fill the gap of real-world high-quality PAL images for low-level vision. A comprehensive variety of experiments on synthetic and real-world benchmarks demonstrates the impressive imaging results of PCIE and the effectiveness of the PSF representation. We further deliver heuristic experimental findings for minimalist and high-quality panoramic imaging, in terms of the choices of prototype and pipeline, network architecture, training strategies, and dataset construction. Our dataset and code will be available at https://***/zju-jiangqi/PCIE-PART. Copyrig

关键词： Optical transfer function

来源：评论

学校读者我要写书评

暂无评论

An extended PI model for hysteresis and creep compensation in AFM based nanomanipulation

An extended PI model for hysteresis and creep compensation i...

引用

IEEE International Conference on robotics and Biomimetics

作者： Zhiyu Wang Lianqing Liu Zhidong Wang Zaili Dong Shuai Yuan Faculty of Electrical and Control Engineering Liaoning Technical University Huludao China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy and Sciences Shenyang China Chinese Academy and Sciences Beijing China Department of Advanced Robotics Chiba Institute of Technology Chiba Japan Chinese Academy of Sciences Beijing Beijing CN

ISBN: (纸本)9781424493197

One of the prerequisites for AFM based nanomanipulation is that the tip position can be controlled accurately, while this prerequisite is still hindered by the large model uncertainties aroused from PZT nonlinearity such as hysteresis and creep. In this paper, an Extended Prandtl-Ishlinskii (EPI) model is proposed to solve these problems. The main advantage of EPI model over conventional PI model is that the EPI model can compensate the positioning error caused by hysteresis and creep simultaneously through adopting the new adaptive basic operator. The experimental results demonstrate the effectiveness and validity of EPI model in depicting the PZT hysteresis and creep prosperities.

关键词： Creep Hysteresis Fitting Data models Adaptation model Robot sensing systems

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：