检索结果-内蒙古大学图书馆

A Mars Multi-terrain Simulator Using a Modular Terrain Construction Framework

学校读者我要写书评

暂无评论

A Mars Multi-terrain Simulator Using a Modular Terrain Const...

On-Line Conference (ONCON), Industrial Electronics Society Annual

作者： Yun Jiang Meibao Yao Bo Zheng Tao Hu Tao Cao Xueming Xiao Intelligent Robotics Lab (IRL) School of Artificial Intelligence Jilin University Changchun China Engineering Research Center of Knowledge-Driven Human-Machine Intelligence Ministry of Education China Shanghai Aerospace Control Technology Institute Shanghai China CVIR Lab Changchun University of Science and Technology Changchun China Key Lab of Optoelectronic Measurement and Optical Information Transmission Technology

Mars exploration tasks are inseparable from the support of robotic equipment. More comprehensive environmental awareness capabilities can improve the efficiency of robots on the surface of Mars. Artificial neural networks have emerged as pivotal tools in enhancing the perceptual capabilities of robots. The cornerstone of effective neural network training lies in the availability of high-quality data. Regrettably, the unstructured terrains, particularly the Martian landscape, lack real-world datasets with high-quality annotations. To overcome this challenge, using simulators to generate large amounts of high-quality data for researchers is a good option. Nonetheless, the creation of these simulators requires complex details such as ground texture characteristics and rock distribution, which increases research costs. In response, we introduce a novel approach – the modular terrain construction framework and construct a Mars multi-terrain simulator based on it. This innovative simulator not only simplifies the simulation process but also grants users the flexibility to alter it to their specific research needs. One of the standout features of our simulator is its capacity to generate rich metadata, such as semantic and depth, which can be used seamlessly for a multitude of downstream applications. To validate the reliability of the data produced by our simulator, we have assessed its performance on a semantic segmentation task.

关键词：

Co-Optimization Method for Modular Robots Based on Evolutionary Algorithm

学校读者我要写书评

暂无评论

Co-Optimization Method for Modular Robots Based on Evolution...

On-Line Conference (ONCON), Industrial Electronics Society Annual

作者： Peng Zhao Meibao Yao Bo Zheng Xueming Xiao Intelligent Robotics Lab (IRL) School of Artificial Intelligence Jilin University Changchun China Engineering Research Center of Knowledge-Driven Human-Machine Intelligence Ministry of Education China Shanghai Aerospace Control Technology Institute Shanghai China CVIR Lab Changchun University of Science and Technology Changchun China Key Lab of Optoelectronic Measurement and Optical Information Transmission Technology

Deploying robots instead of human labor in complex and hazardous environments is a highly effective strategy. However, current fixed-configuration robot platforms struggle to meet the demanding exploration requirements in non-structured environments. In contrast, reconfigurable modular robots are able to adjust their configurations in response to environmental and task requirements, thereby offering immense potential for tackling complex exploration tasks in unstructured environments. This versatility of reconfigurable modular robots allows them to better adapt to various environmental and task demands, such as using snake or caterpillar configurations to navigate narrow holes, or quadruped configurations to traverse rugged terrain. However, the current research on modular robots primarily focuses on optimizing either their own configurations or solely the motion control model, potentially limiting their adaptability to the environment and hindering the full realization of their reconfigurability. To address this limitation, this paper improves upon traditional EA and proposes a configuration-motion co-optimization method and a new encoding method for modular robots, which jointly models and optimizes both configuration and motion. The method includes dynamic encoding of configuration-motion and the design of compatible operators, effectively enhancing the adaptive capabilities of modular robots in complex environments. The method was validated using the Webots platform, and the results demonstrate successful generation of adaptable reconfiguration schemes for various terrains. Compared to traditional EA, this method has shown superior performance in handling diverse tasks.

关键词：

WCEBleedGen: A wireless capsule endoscopy dataset and its benchmarking for automatic bleeding classification, detection, and segmentation

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Handa, Palak Dhir, Manas Mahbod, Amirreza Schwarzhans, Florian Woitek, Ramona Goel, Nidhi Gunjan, Deepak Research Center for Medical Image Analysis and Artificial Intelligence Department of Medicine Danube Private University Krems Austria Department of Artificial Intelligence and Machine Learning University School of Automation and Robotics Guru Gobind Singh Indraprastha University Delhi India Department of Electronics and Communication Engineering Indira Gandhi Delhi Technical University for Women Delhi India Department of Gastroenterology HNU All India Institute of Medical Sciences Delhi India

Objective: Computer-based analysis of Wireless Capsule Endoscopy (WCE) is crucial. However, a medically annotated WCE dataset for training and evaluation of automatic classification, detection, and segmentation of bleeding and non-bleeding frames is currently lacking. Methods: The present work focused on development of a medically annotated WCE dataset called WCEbleedGen for automatic classification, detection, and segmentation of bleeding and non-bleeding frames. It comprises 2,618 WCE bleeding and non-bleeding frames which were collected from various internet resources and existing WCE datasets. A comprehensive benchmarking and evaluation of the developed dataset was done using nine classification-based, three detection-based, and three segmentation-based deep learning models. Results: The dataset is of high-quality, is class-balanced and contains single and multiple bleeding sites. Overall, our standard benchmark results show that Visual Geometric Group (VGG) 19, You Only Look Once version 8 nano (YOLOv8n), and Link network (Linknet) performed best in automatic classification, detection, and segmentation-based evaluations, respectively. Conclusion and significance: Automatic bleeding diagnosis is crucial for WCE video interpretations. This diverse dataset will aid in developing of real-time, multi-task learning-based innovative solutions for automatic bleeding diagnosis in WCE. The dataset and code are publicly available here. © 2024, CC BY-NC-SA.

关键词： Endoscopy

Hypergraph-based Multi-View Action Recognition using Event Cameras

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Gao, Yue Lu, Jiaxuan Li, Siqi Li, Yipeng Du, Shaoyi BNRist THUIBCS BLBCI School of Software Tsinghua University Beijing100084 China Shanghai Artificial Intelligence Laboratory Shanghai200232 China BNRist THUIBCS BLBCI Department of Automation Tsinghua University Beijing100084 China Department of Ultrasound The Second Affiliated Hospital of Xi’an Jiaotong University China National Key Laboratory of Human-Machine Hybrid Augmented Intelligence National Engineering Research Center for Visual Information and Applications Institute of Artificial Intelligence and Robotics Xi’an Jiaotong University Xi’an710049 China

Action recognition from video data forms a cornerstone with wide-ranging applications. Single-view action recognition faces limitations due to its reliance on a single viewpoint. In contrast, multi-view approaches capture complementary information from various viewpoints for improved accuracy. Recently, event cameras have emerged as innovative bio-inspired sensors, leading to advancements in event-based action recognition. However, existing works predominantly focus on single-view scenarios, leaving a gap in multi-view event data exploitation, particularly in challenges like information deficit and semantic misalignment. To bridge this gap, we introduce HyperMV, a multi-view event-based action recognition framework. HyperMV converts discrete event data into frame-like representations and extracts view-related features using a shared convolutional network. By treating segments as vertices and constructing hyperedges using rule-based and KNN-based strategies, a multi-view hypergraph neural network that captures relationships across viewpoint and temporal features is established. The vertex attention hypergraph propagation is also introduced for enhanced feature fusion. To prompt research in this area, we present the largest multi-view event-based action dataset THUMV-EACT-50, comprising 50 actions from 6 viewpoints, which surpasses existing datasets by over tenfold. Experimental results show that HyperMV significantly outperforms baselines in both cross-subject and cross-view scenarios, and also exceeds the state-of-the-arts in frame-based multi-view action recognition. Copyright © 2024, The Authors. All rights reserved.

关键词： Cameras

LPL-SLAM: LiDAR SLAM with Plane and Line Optimization for Structural Environment

学校读者我要写书评

暂无评论

LPL-SLAM: LiDAR SLAM with Plane and Line Optimization for St...

On-Line Conference (ONCON), Industrial Electronics Society Annual

作者： Huanfeng Zhao Meibao Yao Xueming Xiao Bo Zheng Tao Cao Tao Hu Intelligent Robotics Lab (IRL) School of Artificial Intelligence Jilin University Changchun China Engineering Research Center of Knowledge-Driven Human-Machine Intelligence Ministry of Education China CVIR Lab Changchun University of Science and Technology Changchun China Key Lab of Opto-Electronic Measurement and Optical Information Transmission Technology Shanghai Aerospace Control Technology Institute Shanghai China

In LiDAR SLAM, data association of sparse LiDAR scan and high computational complexity of point-to-model metrics limit real-time applications of joint optimization module like Bundle Adjustment in Visual SLAM, which leads to cumulative errors deteriorating performance. To address this drawback, in this paper, we propose LPL-SLAM with plane and line optimization for the structural environment. Since plane and line primitives are ubiquitous in man-made environments, we treat the primitives as landmarks to process scans. We introduce line and plane factors relying on line-to-line and plane-to-plane metrics to optimize keyframe poses, planes and lines. With the line and plane factors, our system avoids a large-scale optimization problem and yields accurate and consistent tracking poses. Experimental results demonstrate that LPL-SLAM outperforms the state-of-the-art algorithms and achieves real-time performance.

关键词：

To Sparsify or not to Sparsify: Simplifying Visual Feature Maps for Mobile Agents

学校读者我要写书评

暂无评论

To Sparsify or not to Sparsify: Simplifying Visual Feature M...

IEEE International Symposium on Multimedia

作者： Sebastian Eger Rastin Pries Gábor Sörös Michael G. Adam Martin Piccolrovazzi Eckehard Steinbach Department of Computer Engineering Chair of Media Technology Munich Institute of Robotics and Machine Intelligence (MIRMI) School of Computation Information and Technology Technical University of Munich Nokia Bell Labs Munich Germany Nokia Bell Labs Budapest Hungary

ISBN: (纸本)9781665471732

Real-time pose estimation is crucial for autonomous agents for motion control and navigation, and it is essential for extended reality applications as well. As the current global positioning systems are not reliable indoors or are not precise enough, visual simultaneous localization and mapping is becoming prevalent in autonomous agents and mobile devices. The visual feature maps can be shared between agents and might be merged into a common map on a server and redistributed to all clients to enable re-localization and co-localization. However, merged maps can grow continuously in density and size that constrained agents are not able to handle *** this paper, we investigate how the map density effects localization and visual odometry performance on low-cost mobile clients. We show that a sparse representation of the original VFM is necessary for real-time visual odometry but at the cost of a degraded re-localization performance.

关键词： Visualization Simultaneous localization and mapping Mobile agents Pose estimation Real-time systems Mobile handsets Autonomous agents

Polarization-independent resonant lattice Kerker effect in phase-change metasurface

学校读者我要写书评

暂无评论

arXiv 2022年

作者： Xiong, Lei Luo, Xiaoqing Ding, Hongwei Lu, Yuanfu Li, Guangyuan School of Information Science and Engineering Yunnan University Kunming650500 China Cas Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Siat Branch Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen518055 China

Resonant lattice Kerker effect in periodic resonators is one of the most interesting generalizations of the Kerker effect that relates to various fascinating functionalities such as scattering management and Huygens metasurfaces. However, so far this effect has been shown to be sensitive to the incident polarization, restricting its applications. Here, we report, for the first time, polarization-independent resonant lattice Kerker effect in metasurfaces composed of periodic Ge2Se2Te5(GST) disks. For such a metasurface of square lattice, the spectrally overlap of the electric dipole and magnetic dipole surface lattice resonances can be realized by choosing an appropriate GST crystalline fraction regardless of the incident polarization. The operation wavelength and the required GST crystalline fraction can be conveniently tuned over large ranges since these parameters scale linearly with the disk size and the lattice period, greatly facilitating the design. Making use of the obtained resonant lattice Kerker effect, we realize a reconfigurable and polarization-independent lattice Huygens' metasurface with a dynamic phase modulation of close to 2π and high transmittance. This work will advance the engineering of the resonant lattice Kerker effect and promote its applications in phase modulation and wavefront control. Copyright © 2022, The Authors. All rights reserved.

关键词： Tellurium compounds

Optimal UAV hitching on ground vehicles

学校读者我要写书评

暂无评论

arXiv 2021年

作者： Ruan, Lihua Duan, Lingjie Huang, Jianwei School of Science and Engineering Shenzhen Institute of Artificial Intelligence and Robotics for Society The Chinese University of Hong Kong Shenzhen China University of Science and Technology of China Hefei China The Engineering Systems and Design Pillar Singapore University of Technology and Design Singapore The Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen China School of Science and Engineering Shenzhen Institute of Artificial Intelligence and Robotics for Society The Chinese University of Hong Kong Shenzhen518172 China

Due to its mobility and agility, unmanned aerial vehicle (UAV) has emerged as a promising technology for various tasks, such as sensing, inspection and delivery. However, a typical UAV has limited energy storage and cannot fly a long distance without being recharged. This motivates several existing proposals to use trucks and other ground vehicles to offer riding to help UAVs save energy and expand the operation radius. We present the first theoretical study regarding how UAVs should optimally hitch on ground vehicles, considering vehicles' different travelling patterns and supporting capabilities. For a single UAV, we derive closed-form optimal vehicle selection and hitching strategy. When vehicles only support hitching, a UAV would prefer the vehicle that can carry it closest to its final destination. When vehicles can offer hitching plus charging, the UAV may hitch on a vehicle that carries it farther away from its destination and hitch a longer distance. The UAV may also prefer to hitch on a slower vehicle for the benefit of battery recharging. For multiple UAVs in need of hitching, we develop the max-saving algorithm (MSA) to optimally match UAV-vehicle collaboration. We prove that the MSA globally optimizes the total hitching benefits for the UAVs. © 2021, CC BY.

关键词： Energy conservation

A Novel Duo-Stage driven Deep Neural Network Approach for Mitigating Electrode Shift Impact on Myoelectric Pattern Recognition Systems

学校读者我要写书评

暂无评论

A Novel Duo-Stage driven Deep Neural Network Approach for Mi...

IEEE International Workshop on Medical Measurement and Applications (MEMEA)

作者： Frank Kulwa Oluwarotimi Williams Samuel Mojisola Grace Asogbon Tolulope Tofunmi Oyemakinde Olumide Olayinka Obe Guanglin Li CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen Institute of Advanced Technology (SIAT) Chinese Academy of Sciences (CAS) Shenzhen Guangdong China Shenzhen College of Advanced Technology University of Chinese Academy of Sciences Shenzhen Guangdong China School of Computing and Engineering University of Derby Derby United Kingdom Department of Computer Science Federal University of Technology Akure Nigeria

A major barrier to the commercialization of pattern recognition (PR)-based myoelectric prostheses is the lack of robustness to confounding factors such as electrode shift which has been lingering for years. To overcome this challenge, a novel Duo-Stage Convolutional Neural Network (DS-CNN) is proposed. The DS-CNN is comprised of two cascaded stages in which the first stage deciphers the occurrence of a particular kind of shift upon which a requisite CNN model is triggered in the second stage for accurate decoding of individual motion intent, which is necessary for initiating robust control of the prostheses. The proposed scheme works on raw EMG signals as input which reduces the preprocessing time that would be required in conventional machine learning-based PR schemes, to effectively mitigate both transverse and longitudinal shifts using the same network architecture. This approach was validated for four distinct electrode shift conditions (with shifts in the range of 7.50mm-10.05mm) in a dataset obtained from 18 able-bodied subjects that performed 8 classes of targeted hand gestures. The experimental results show that the proposed dual-stage driven deep neural network model can adequately resolve the effects of electrode shift with classification accuracy near the No-shift scenario (< 1.70% difference between shift mitigation and No shift scenarios). These outcomes suggest that our method can provide a practical solution for adaptation to electrode shift, thus improving the robustness of the EMG pattern recognition systems in both clinical and commercial settings.

关键词：