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arXiv 2025年

作者： Wang, Ruoyu Ma, Yukai Yao, Yi Tao, Sheng Li, Haoang Zhu, Zongzhi Liu, Yong Zuo, Xingxing Institute of Cyber-Systems and Control Zhejiang University Hangzhou China School of Computation Information and Technology Technical University of Munich Munich Germany Zhejiang Guoli Security Technology Co. Ltd. Ningbo China State Key Laboratory of Industrial Control Technology China

Semantic Scene Completion (SSC) constitutes a pivotal element in autonomous driving perception systems, tasked with inferring the 3D semantic occupancy of a scene from sensory data. To improve accuracy, prior research has implemented various computationally demanding and memory-intensive 3D operations, imposing significant computational requirements on the platform during training and testing. This paper proposes L2COcc, a lightweight camera-centric SSC framework that also accommodates LiDAR inputs. With our proposed efficient voxel transformer (EVT) and cross-modal knowledge modules, including feature similarity distillation (FSD), TPV distillation (TPVD) and prediction alignment distillation (PAD), our method substantially reduce computational burden while maintaining high accuracy. The experimental evaluations demonstrate that our proposed method surpasses the current state-of-the-art vision-based SSC methods regarding accuracy on both the SemanticKITTI and SSCBench-KITTI-360 benchmarks, respectively. Additionally, our method is more lightweight, exhibiting a reduction in both memory consumption and inference time by over 23% compared to the current state-of-the-arts method. Code is available at our project page: https://***/L2COcc/. © 2025, CC BY.

关键词： Benchmarking

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Quantity-Aware Coarse-to-Fine Correspondence for Image-to-Point Cloud Registration

arXiv

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arXiv 2023年

作者： Yao, Gongxin Xuan, Yixin Chen, Yiwei Pan, Yu The State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control College of Control Science and Engineering Zhejiang University Hangzhou310027 China The Research Institute of Signals Sensors and Systems Heriot-Watt University United Kingdom

Image-to-point cloud registration aims to determine the relative camera pose between an RGB image and a reference point cloud, serving as a general solution for locating 3D objects from 2D observations. Matching individual points with pixels can be inherently ambiguous due to modality gaps. To address this challenge, we propose a framework to capture quantity-aware correspondences between local point sets and pixel patches and refine the results at both the point and pixel levels. This framework aligns the high-level semantics of point sets and pixel patches to improve the matching accuracy. On a coarse scale, the set-to-patch correspondence is expected to be influenced by the quantity of 3D points. To achieve this, a novel supervision strategy is proposed to adaptively quantify the degrees of correlation as continuous values. On a finer scale, point-to-pixel correspondences are refined from a smaller search space through a well-designed scheme, which incorporates both resampling and quantity-aware priors. Particularly, a confidence sorting strategy is proposed to proportionally select better correspondences at the final stage. Leveraging the advantages of high-quality correspondences, the problem is successfully resolved using an efficient Perspective-n-Point solver within the framework of random sample consensus (RANSAC). Extensive experiments on the KITTI Odometry and NuScenes datasets demonstrate the superiority of our method over the state-of-the-art methods. Copyright © 2023, The Authors. All rights reserved.

关键词： Pixels

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ERASOR++: Height Coding Plus Egocentric Ratio Based Dynamic Object Removal for Static Point Cloud Mapping

arXiv

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arXiv 2024年

作者： Zhang, Jiabao Zhang, Yu State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou China Key Laboratory of Collaborative Sensing and Autonomous Unmanned Systems of Zhejiang Province Hangzhou China

Mapping plays a crucial role in location and navigation within automatic systems. However, the presence of dynamic objects in 3D point cloud maps generated from scan sensors can introduce map distortion and long traces, thereby posing challenges for accurate mapping and navigation. To address this issue, we propose ERASOR++, an enhanced approach based on the Egocentric Ratio of Pseudo Occupancy for effective dynamic object removal. To begin, we introduce the Height Coding Descriptor, which combines height difference and height layer information to encode the point cloud. Subsequently, we propose the Height Stack Test, Ground Layer Test, and Surrounding Point Test methods to precisely and efficiently identify the dynamic bins within point cloud bins, thus overcoming the limitations of prior approaches. Through extensive evaluation on open-source datasets, our approach demonstrates superior performance in terms of precision and efficiency compared to existing methods. Furthermore, the techniques described in our work hold promise for addressing various challenging tasks or aspects through subsequent migration. Copyright © 2024, The Authors. All rights reserved.

关键词： Mapping

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LI-GS: Gaussian Splatting with LiDAR Incorporated for Accurate Large-Scale Reconstruction

arXiv

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arXiv 2024年

作者： Jiang, Changjian Gao, Ruilan Shao, Kele Wang, Yue Xiong, Rong Zhang, Yu State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou China Key Laboratory of Collaborative sensing and autonomous unmanned systems of Zhejiang Province Hangzhou China

Large-scale 3D reconstruction is critical in the field of robotics, and the potential of 3D Gaussian Splatting (3DGS) for achieving accurate object-level reconstruction has been demonstrated. However, ensuring geometric accuracy in outdoor and unbounded scenes remains a significant challenge. This study introduces LI-GS, a reconstruction system that incorporates LiDAR and Gaussian Splatting to enhance geometric accuracy in large-scale scenes. 2D Gaussain surfels are employed as the map representation to enhance surface alignment. Additionally, a novel modeling method is proposed to convert LiDAR point clouds to plane-constrained multimodal Gaussian Mixture Models (GMMs). The GMMs are utilized during both initialization and optimization stages to ensure sufficient and continuous supervision over the entire scene while mitigating the risk of over-fitting. Furthermore, GMMs are employed in mesh extraction to eliminate artifacts and improve the overall geometric quality. Experiments demonstrate that our method outperforms state-of-the-art methods in large-scale 3D reconstruction, achieving higher accuracy compared to both LiDAR-based methods and Gaussian-based methods with improvements of 52.6% and 68.7%, respectively. Copyright © 2024, The Authors. All rights reserved.

关键词： Optical radar

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A Study of Structured Surface Generation on Tungsten Carbide by Electrical Discharge Machining with Self-assemble Ball Electrodes 38

A Study of Structured Surface Generation on Tungsten Carbide...

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38th Annual Meeting of the American Society for Precision Engineering, ASPE 2023

作者： Li, Kangsen Cheung, Chi Fai Wang, Chunjin Gong, Feng State key Laboratory of Ultra-precision Machining Technology Department of Industrial and Systems Engineering Hongkong Polytechnic University Hong Kong Hong Kong Shenzhen Key Laboratory of High Performance Nontraditional Manufacturing College of Mechatronics and Control Engineering Shenzhen University Guangdong Shenzhen China

ISBN: (纸本)9781887706599

Electrical discharge machining (EDM) has been extensively utilized in the precision manufacturing of difficult-to-cut material. The preparation of electrodes is of great importance for structured surface generation after EDM. Electrode wear is an inevitable problem, which affects the machining accuracy and efficiency of the workpiece. Therefore, the design and optimization of the electrodes are vital for the EDM process. In this paper, a novel self-assembly ball electrode for EDM of the structured array on the binderless tungsten carbide (WC) is proposed. The shape evolution and surface roughness of the structured surface was investigated. The result indicates that self-assembly ball electrodes have a great advantage in machining the structured surface arrays. © 2023 Proceedings - ASPE 2023 Annual Meeting. All rights reserved.

关键词： Tungsten carbide

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ERASOR++: Height Coding Plus Egocentric Ratio Based Dynamic Object Removal for Static Point Cloud Mapping

ERASOR++: Height Coding Plus Egocentric Ratio Based Dynamic ...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Jiabao Zhang Yu Zhang State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou China Key Laboratory of Collaborative Sensing and Autonomous Unmanned Systems of Zhejiang Province Hangzhou China

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

关键词： Point cloud compression Technological innovation Accuracy Three-dimensional displays Image analysis Navigation Encoding

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All-weather,natural silent speech recognition via machine-learning-assisted tattoo-like electronics

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npj Flexible Electronics 2021年第1期5卷 183-191页

作者： Youhua Wang Tianyi Tang Yin Xu Yunzhao Bai Lang Yin Guang Li Hongmiao Zhang Huicong Liu YongAn Huang State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhanChina Flexible Electronics Research Center Huazhong University of Science and TechnologyWuhanChina School of Mechanical and Electric Engineering Jiangsu Provincial Key Laboratory of Advanced RoboticsSoochow UniversitySuzhouChina State Key Laboratory of Industrial Control Technologyg Institute of Cyber Systems and ControlZhejiang UniversityHangzhouChina

The internal availability of silent speech serves as a translator for people with aphasia and keeps human–machine/human interactions working under various *** paper develops a silent speech strategy to achieve all-weather,natural *** strategy requires few usage specialized skills like sign language but accurately transfers high-capacity information in complicated and changeable daily *** the strategy,the tattoo-like electronics imperceptibly attached on facial skin record high-quality bio-data of various silent speech,and the machine-learning algorithm deployed on the cloud recognizes accurately the silent speech and reduces the weight of the wireless acquisition module.A series of experiments show that the silent speech recognition system(SSRS)can enduringly comply with large deformation(~45%)of faces by virtue of the electricitypreferred tattoo-like electrodes and recognize up to 110 words covering daily vocabularies with a high average accuracy of 92.64%simply by use of small-sample machine *** successfully apply the SSRS to 1-day routine life,including daily greeting,running,dining,manipulating industrial robots in deafening noise,and expressing in darkness,which shows great promotion in real-world applications.

关键词： translator weather silent

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BEVTransFusion: LiDAR-Camera Fusion Under Bird’s-Eye-View for 3D Object Detection with Transformers

BEVTransFusion: LiDAR-Camera Fusion Under Bird’s-Eye-View f...

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Pattern Recognition and Machine Learning (PRML), IEEE International Conference on

作者： Kaiqi Feng Yu Zhang State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou China State Key Laboratory of Industrial Control Technology Key Laboratory of Collaborative sensing and autonomous unmanned systems of Zhejiang Province College of Control Science and Engineering Zhejiang University Hangzhou China

Recently, there is growing research interest in extracting Bird’s-Eye-View (BEV) features from images and LiDAR to improve 3D object detection. However, existing methods mainly combine the features mechanically, which limits the utilization of BEV features. To address this limitation, we draw inspiration from TransFusion and design a two-layer transformer decoder to fuse LiDAR and camera BEV features. By doing so, we can omit the steps of reference point backprojection and feature sampling, which results in better correlation between the fused LiDAR and image features and higher robustness to the calibration matrix. Furthermore, we add 3D position encoding to the BEV features to compensate for the lack of height information. We also propose an length-width-height modulated attention mechanism to incorporate scale information. We also perform comprehensive experiments to verify the effectiveness of our methods.

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Dynamic Performance Prediction in Batch-Based Assembly System with Bernoulli Machines and Changeovers

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Complex System Modeling and Simulation 2022年第3期2卷 224-237页

作者： Zunjun Wang Zhiyang Jia Xiuxuan Tian Jingchuan Chen Bei Pan State Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of TechnologyBeijing 100081China Department of Industrial and Manufacturing Systems Engineering University of Hong KongHong Kong 999077China School of Engineering Tokyo University of TechnologyTokyo 192-0982Japan

Worldwide competition and diverse demand of customers pose great challenges to manufacturing enterprises. How to organize production to achieve high productivity and low cost becomes their primary task. In the mean time, the rapid pace of technology innovation has contributed to the development of new types of flexible automation. Hence, increasing manufacturing enterprises convert to multi-product and small-batch production, a manufacturing strategy that brings increased output, reduced costs, and quick response to the market. A distinctive feature of small-batch production is that the system operates mainly in the transient states. Transient states may have a significant impact on manufacturing systems. It is therefore necessary to estimate the dynamic performance of systems. As the assembly system is a typical class of production systems, in this paper, we focus on the problem of dynamic performance prediction of the assembly systems that produce small batches of different types of products. And the system is assumed to be characterized with Bernoulli reliability machines, finite buffers, and changeovers. A mathematical model based on Markovian analysis is first derived and then, the analytical formulas for performance evaluation of three-machine assembly systems are given. Moreover, a novel approach based on decomposition and aggregation is proposed to predict dynamic performance of large-scale assembly systems that consist of multiple component lines and additional processing machines located downstream of the assemble machine. The proposed approach is validated to be highly accurate and computationally efficient when compared to Monte Carlo simulation.

关键词： flexible assembly system dynamic performance Bernoulli machines finite buffers changeovers

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A Monocular Biological Simultaneous Localization and Mapping Method Based on a Bionic Vision Model

A Monocular Biological Simultaneous Localization and Mapping...

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Frontiers of Robotics and Software Engineering (FRSE), International Conference on

作者： Sitong Guo Yu Zhang State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou China State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Key Laboratory of Collaborative sensing and autonomous unmanned systems of Zhejiang Province Hangzhou China

Animals can navigate robustly through large unknown environments, utilizing inaccurate sensor and egomotion cues. Inspired by the mechanism of the human visual system, this paper presents a biological simultaneous localization and mapping (SLAM) system based on a monocular vision sensor to perform navigation tasks in complex environments. Specifically, our contributions are two folds: an improved monocular visual odometry with a scale recovery algorithm to calibrate the estimated robot pose, and a bionic vision model based on image enhancement algorithm and feature extraction approach to detect closed-loop. Experiments on public datasets demonstrate that our proposed method performs competitively in illumination-varying scenarios indoors and outdoors, which achieve a trade-off to maintain performances in terms of accuracy, execution time, and robustness.

关键词：

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